Alternatives to claude-mem

Compare claude-mem alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to claude-mem in 2026. Compare features, ratings, user reviews, pricing, and more from claude-mem competitors and alternatives in order to make an informed decision for your business.

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    Gemini Enterprise Agent Platform
    Gemini Enterprise Agent Platform is a comprehensive solution from Google Cloud designed to help organizations build, scale, govern, and optimize AI agents. It represents the evolution of Vertex AI, combining advanced model development with new capabilities for agent orchestration and integration. The platform provides access to over 200 leading AI models, including Google’s Gemini series and third-party options like Anthropic’s Claude. It enables teams to create intelligent agents using both low-code and code-first development environments. With features like Agent Runtime and Memory Bank, businesses can deploy long-running agents that retain context and perform complex workflows. The platform emphasizes security and governance through tools like Agent Identity, Agent Registry, and Agent Gateway. It also includes optimization tools such as simulation, evaluation, and observability to ensure consistent agent performance.
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    Amp

    Amp

    Amp Code

    Amp is a frontier coding agent built to give developers full access to the power of today’s leading AI models directly in their workflow. Available in the terminal and popular editors like VS Code, Cursor, Windsurf, JetBrains, and Neovim, Amp integrates seamlessly into existing development environments. It enables developers to delegate complex coding tasks, refactors, reviews, and explorations to intelligent agents that understand and operate across entire codebases. With support for advanced models such as Claude Opus, Gemini, and GPT-class models, Amp delivers fast, reliable, and highly agentic code generation. The platform is designed for real-world engineering work, handling multi-file changes, deep context, and iterative improvements. Amp helps developers move faster while maintaining confidence in code quality.
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    CMEM Cloud

    CMEM Cloud

    cmem.ai

    CMEM Cloud is the cloud sync layer for claude-mem, built to link AI agent memory everywhere through one private MCP link. claude-mem is the open source engine that takes notes while an agent works, and CMEM Cloud mirrors that local memory so agents can recall it across every session, machine, editor, and MCP-compatible client. Instead of making users re-explain context, paste old notes, or restart from zero, the system captures decisions, bug fixes, dead ends, environment notes, architecture choices, and other structured observations as the agent works. Those observations are stored in a temporal database, searched by meaning through vector recall, and made available through a private MCP endpoint that any compatible agent can read and write through. It starts with installing the local engine, letting a second model write structured notes out of band, syncing the local database to CMEM Cloud, and then recalling that memory anywhere.
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    PlatformPilot
    PlatformPilot is a company brain for AI-first teams. It captures how your company actually works, your decisions, playbooks, and tribal knowledge, and turns it into a living memory your team and your AI agents can use to answer questions and take action across all your tools. Unlike search tools that only retrieve, PlatformPilot reasons across your systems, shows the why behind every answer, and acts on your own playbooks, in your own cloud, getting sharper every time it is used. It connects to your stack through the Model Context Protocol (MCP), so it works as a shared memory layer inside the tools your team already uses, including Claude Code, Claude Desktop, and OpenAI-based agents. Memory evolves as you work. - Living memory that learns from outcomes, not just stores notes - Reasoning across all your tools. We support +200 tools. - Plain-language search over your team's decisions, playbooks, and history - Self-organizing knowledge
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    Graphify

    Graphify

    Graphify

    Graphify is an open source knowledge graph engine that turns any input, including code, docs, papers, meetings, images, browser tabs, and commits, into one traversable graph with complete recall. It is built as persistent memory for AI coding assistants, giving tools like Claude Code, Codex, OpenCode, Cursor, Gemini CLI, GitHub Copilot CLI, Aider, Factory Droid, Kimi Code, Kiro, Pi, and Google Antigravity a queryable understanding of a project instead of making them repeatedly grep through files. Users can point Graphify at any directory, and it builds an initial corpus through AST extraction, semantic analysis, and Leiden clustering, transforming an entire codebase or document corpus into a graph in one pass. Unlike RAG pipelines that re-embed everything on every change, Graphify maintains a living graph that updates only affected nodes and edges when files change, allowing the rest of the corpus to stay intact even at enterprise scale.
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    OpenMemory

    OpenMemory

    OpenMemory

    OpenMemory is a Chrome extension that adds a universal memory layer to browser-based AI tools, capturing context from your interactions with ChatGPT, Claude, Perplexity and more so every AI picks up right where you left off. It auto-loads your preferences, project setups, progress notes, and custom instructions across sessions and platforms, enriching prompts with context-rich snippets to deliver more personalized, relevant responses. With one-click sync from ChatGPT, you preserve existing memories and make them available everywhere, while granular controls let you view, edit, or disable memories for specific tools or sessions. Designed as a lightweight, secure extension, it ensures seamless cross-device synchronization, integrates with major AI chat interfaces via a simple toolbar, and offers workflow templates for use cases like code reviews, research note-taking, and creative brainstorming.
    Starting Price: $19 per month
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    Membase

    Membase

    Membase

    Membase is a unified AI memory layer platform designed to help AI agents and tools share and persist context so they “understand you” across sessions without forced repetition or isolated memory silos, enabling consistent conversational experiences and shared knowledge across AI assistants. It provides a secure, centralized memory layer that captures, stores, and syncs context, conversation history, and relevant knowledge across multiple AI agents and integrations with tools such as ChatGPT, Claude, Cursor, and others, so all connected agents can access a common context and avoid repeating user intents. Designed as a foundational memory service, it aims to maintain consistent context across your AI ecosystem, reducing friction and improving continuity in multi-tool workflows by keeping long-term context available and shared rather than locked within individual models or sessions, and letting users focus on outcomes instead of re-entering context for each agent request.
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    Vokal

    Vokal

    Vokal

    Vokal is a collaboration space for teammates and AI agents, built so founders and product teams can run agent work where the team can see it, review it, and reuse what matters. It gives human-agent work a shared place to start, move, stay visible, and become reusable context, instead of leaving agent runs, assumptions, and decisions trapped in private sessions across Claude Code, Codex, Cursor, ChatGPT, or other tools. Vokal connects channels, tasks, docs, files, apps, agents, memory, Knowledge Base, identity, access, runtime, and event logs around the work, helping teams keep output aligned, reviewed, controlled, and reusable. Agents can work in shared channels with named owners, roles, instructions, sources, statuses, permission scopes, app grants, memory scope, local project-file grants, and visible activity. Teams can use pre-built roles for engineering, product, growth, support, operations, research, and customer work, or bring their own local Codex, Claude Code, Hermes, etc.
    Starting Price: $20 per month
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    Preloop

    Preloop

    Preloop

    Preloop is the open source AI agent control plane for agents that take real actions. It combines an MCP firewall for tool access, an AI model gateway for cost, safety, and attribution, policy-as-code with human approvals, runtime session observability, and audit trails in a single self-hostable platform. AI agents can deploy code, change infrastructure, move money, touch production data, and burn model spend in seconds, so Preloop helps teams control what agents can do, how much they spend, and which actions require human approval. It works with OpenClaw, Hermes, Claude Code, Codex CLI, Cursor, Gemini CLI, Windsurf, Cline, OpenCode, and any MCP-compatible agent or managed runtime. Access rules can inspect arguments and context, not just tool names, with CEL expressions for fine-grained conditions. Teams can start with observability, then layer in approvals and deny rules without SDKs or invasive app changes.
    Starting Price: $290 per month
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    HQ

    HQ

    Indigo AI

    HQ is the shared AI context layer for teams, giving the whole team and every AI tool one workspace to work from, with knowledge, skills, and workflows compounding in one place, and any agent running on top. It works as an operating system for AI workers over Claude Code, Cursor, Codex, ChatGPT, and Claude chat through MCP, so every teammate and every agent can start from the same shared context instead of separate chat histories, scattered files, and siloed workflows. HQ turns one person’s best work into team infrastructure: any prompt or workflow can become a reusable /command, then /hq-sync ships it to the whole team so anyone can run it in one step. Knowledge that usually lives across decisions, docs, playbooks, policies, projects, code, and ideas accumulates in HQ as the team works, creating one source of truth that every agent can search, reuse, and build on. Agents can be deployed into email and Slack, acting on top of the team’s skills and knowledge with full context.
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    ByteRover

    ByteRover

    ByteRover

    ByteRover is a self-improving memory layer for AI coding agents that unifies the creation, retrieval, and sharing of “vibe-coding” memories across projects and teams. Designed for dynamic AI-assisted development, it integrates into any AI IDE via the Memory Compatibility Protocol (MCP) extension, enabling agents to automatically save and recall context without altering existing workflows. It provides instant IDE integration, automated memory auto-save and recall, intuitive memory management (create, edit, delete, and prioritize memories), and team-wide intelligence sharing to enforce consistent coding standards. These capabilities let developer teams of all sizes maximize AI coding efficiency, eliminate repetitive training, and maintain a centralized, searchable memory store. Install ByteRover’s extension in your IDE to start capturing and leveraging agent memory across projects in seconds.
    Starting Price: $19.99 per month
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    AgentScreenshots

    AgentScreenshots

    AgentScreenshots

    AgentScreenshots gives AI coding agents a practical visual feedback loop for frontend development. The `agentshot` CLI captures screenshots of localhost, preview, staging, or production pages, saves PNGs into your project, and lets the agent inspect the rendered pixels before claiming the UI is done. It is built for Claude Code, Codex, Cursor, OpenCode, and other coding agents.
    Starting Price: €5/month
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    MemClaw

    MemClaw

    Caura AI

    MemClaw is a persistent-memory service for LLM-based agents and a governed shared memory layer for agent fleets. It is designed to help AI agents learn from each other by turning isolated agent context into a Company Brain with memory, governance, provenance, contradiction detection, and visibility scopes built in from day one. MemClaw separates an organization’s agent force, including tenants, fleets, nodes, and agents, from the governed memory plane through MCP Server, REST API, OpenClaw plugin, MemClaw Core, and persistent storage. Agents can write to and recall from the Company Brain through MCP-compatible tools, direct HTTPS calls, or OpenClaw integration, while MemClaw Core runs enrichment such as entity extraction, contradiction detection, PII scanning, and lifecycle transitions before anything is stored. Every memory can be stamped with a visibility scope, auto-classified into types such as fact, episode, decision, preference, rule, plan, commitment, action, and outcome.
    Starting Price: $49 per month
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    Memory AGI

    Memory AGI

    Memory AGI

    Memory AGI is a runtime memory layer for AI agents, built around the idea of giving agents real muscle memory. Hand over a slice of company data, and Memory AGI builds the organization’s knowledge and runtime memory layer, grounds agents in the business, and keeps that context current automatically. Your AI is only as good as the context you give it; without it, agents stay stuck at an intern-level, guessing at how the company runs. Memory AGI turns processes into knowledge agents that can actually execute, so they run reliably, show their work, and can be trusted with what they ship. It is built on three layers of muscle memory. Dynamic Ingestion captures and structures the company’s unique knowledge from voice notes, internal documents, or the tools where data already lives. The Runtime Memory Layer gives agents access to a live, de-duplicated context layer; a company knowledge base that humans, agents, and automations can all draw on to perform tasks like the best employees.
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    Hindsight

    Hindsight

    Vectorize

    Hindsight is an agent memory system built to create smarter AI agents that learn over time instead of starting every conversation from zero. Most agent memory systems focus on recalling conversation history, but Hindsight is focused on making agents learn, not just remember. It gives AI agents persistent long-term memory using biomimetic data structures, helping them retain facts, recall relevant context, and reflect on experience as part of reasoning. Hindsight is designed for agents that need to understand who a user is, what has been discussed, what preferences have emerged, what decisions were made, and how behavior should adapt across sessions. It provides three core operations: retain, recall, and reflect. Retain stores new information, recall retrieves the right memories when needed, and reflect helps agents synthesize observations, form mental models, and learn from prior interactions.
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    MemPalace

    MemPalace

    MemPalace

    MemPalace is a local-first storage and retrieval system for AI workflows, built to give AI a memory while keeping the user’s words under their own control. It stores conversations verbatim instead of reducing them to summaries, then organizes that memory into a navigable “palace” structure inspired by the ancient memory palace technique. Conversations can be arranged into wings for people, projects, or topics, with rooms and drawers used to make information easier to locate, narrow, and retrieve later. It is designed for people who believe their words are theirs, with local-first storage, zero telemetry, and a privacy-focused approach that keeps memory on the user’s machine. MemPalace supports AI workflows through MCP tooling, including tools for palace reads and writes, knowledge-graph operations, cross-wing navigation, drawer management, and agent diaries.
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    MythOS

    MythOS

    MythOS

    MythOS is a shared memory system between you and every AI you use, built to help people stop re-explaining themselves across models, agents, and channels. It is designed for people who write to think, giving them a modular thinking system for structured notes, memos, contextual maps, and AI-powered workflows. Users can capture what they read, connect what they think, and publish what matters while keeping their library one click away from every AI. MythOS works as a personal knowledge operating system where memory, notes, ideas, resources, and context can be organized into structured documents that stay useful over time. Its approach treats knowledge as a process, not a one-time activity, so living documents can remain in progress, evolve, and connect with related people, projects, topics, and ideas. It supports contextual maps, public memos, private knowledge, AI-ready memory, exportable data, and workflows that help users build a durable layer of context.
    Starting Price: $10 per month
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    Superpowers

    Superpowers

    Superpowers

    Superpowers is an open-source software development methodology and skills framework designed to improve how coding agents plan, build, test, and review software. The project gives AI coding tools a structured workflow that helps them clarify requirements before writing code. It supports agents such as Claude Code, Codex CLI, Codex App, Factory Droid, Gemini CLI, OpenCode, Cursor, and GitHub Copilot CLI. Superpowers guides agents through brainstorming, design approval, implementation planning, test-driven development, subagent-driven execution, code review, and branch completion. Its skills library emphasizes red-green-refactor testing, systematic debugging, isolated git worktrees, verification, and evidence-based completion. Superpowers helps developers turn AI coding agents into more disciplined engineering partners that follow repeatable processes instead of jumping straight into code.
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    Subspace

    Subspace

    Subspace

    Subspace is an AI-native agent workspace designed to help developers and teams manage, coordinate, and collaborate with multiple coding agents in a single unified environment while preserving context across sessions. Instead of treating each AI interaction as isolated, the platform builds persistent memory in the background by compressing every conversation into structured observations such as decisions, blockers, and progress, which are continuously synthesized into a clear, evolving project state. This shared memory belongs to the workspace rather than any individual tool, allowing different agents like Claude Code, Codex, or others to seamlessly pick up where previous sessions left off without requiring repeated explanations or manual context transfer. Subspace integrates terminals, files, documentation, browser views, and git workflows into organized workspaces, enabling users to run multiple agents side by side and switch between projects almost instantly.
    Starting Price: $12 per month
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    LangMem

    LangMem

    LangChain

    LangMem is a lightweight, flexible Python SDK from LangChain that equips AI agents with long-term memory capabilities, enabling them to extract, store, update, and retrieve meaningful information from past interactions to become smarter and more personalized over time. It supports three memory types and offers both hot-path tools for real-time memory management and background consolidation for efficient updates beyond active sessions. Through a storage-agnostic core API, LangMem integrates seamlessly with any backend and offers native compatibility with LangGraph’s long-term memory store, while also allowing type-safe memory consolidation using schemas defined in Pydantic. Developers can incorporate memory tools into agents using simple primitives to enable seamless memory creation, retrieval, and prompt optimization within conversational flows.
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    BrainAPI

    BrainAPI

    Lumen Platforms Inc.

    BrainAPI is the missing memory layer for AI. Large language models are powerful but forgetful — they lose context, can’t carry your preferences across platforms, and break when overloaded with information. BrainAPI solves this with a universal, secure memory store that works across ChatGPT, Claude, LLaMA and more. Think of it as Google Drive for memories: facts, preferences, knowledge, all instantly retrievable (~0.55s) and accessible with just a few lines of code. Unlike proprietary lock-in services, BrainAPI gives developers and users control over where data is stored and how it’s protected, with future-proof encryption so only you hold the key. It’s plug-and-play, fast, and built for a world where AI can finally remember.
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    Letta

    Letta

    Letta

    Create, deploy, and manage your agents at scale with Letta. Build production applications backed by agent microservices with REST APIs. Letta adds memory to your LLM services to give them advanced reasoning capabilities and transparent long-term memory (powered by MemGPT). We believe that programming agents start with programming memory. Built by the researchers behind MemGPT, introduces self-managed memory for LLMs. Expose the entire sequence of tool calls, reasoning, and decisions that explain agent outputs, right from Letta's Agent Development Environment (ADE). Most systems are built on frameworks that stop at prototyping. Letta' is built by systems engineers for production at scale so the agents you create can increase in utility over time. Interrogate the system, debug your agents, and fine-tune their outputs, all without succumbing to black box services built by Closed AI megacorps.
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    Hyperspell

    Hyperspell

    Hyperspell

    Hyperspell is an end-to-end memory and context layer for AI agents that lets you build data-powered, context-aware applications without managing the underlying pipeline. It ingests data continuously from user-connected sources (e.g., drive, docs, chat, calendar), builds a bespoke memory graph, and maintains context so future queries are informed by past interactions. Hyperspell supports persistent memory, context engineering, and grounded generation, producing structured or LLM-ready summaries from the memory graph. It integrates with your choice of LLM while enforcing security standards and keeping data private and auditable. With one-line integration and pre-built components for authentication and data access, Hyperspell abstracts away the work of indexing, chunking, schema extraction, and memory updates. Over time, it “learns” from interactions; relevant answers reinforce context and improve future performance.
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    MemMachine

    MemMachine

    MemVerge

    An open-source memory layer for advanced AI agents. It enables AI-powered applications to learn, store, and recall data and preferences from past sessions to enrich future interactions. MemMachine’s memory layer persists across multiple sessions, agents, and large language models, building a sophisticated, evolving user profile. It transforms AI chatbots into personalized, context-aware AI assistants designed to understand and respond with better precision and depth.
    Starting Price: $2,500 per month
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    OpenViking

    OpenViking

    OpenViking

    OpenViking is an open source context database designed specifically for AI agents, built around a file-system paradigm that unifies the management of memories, resources, and skills. Instead of treating context as scattered chunks in a fragmented vector store, OpenViking organizes agent context into a virtual file system under the viking protocol, giving agents a structured way to store, navigate, retrieve, and observe the information they need. It is designed to help developers move beyond the hassle of manual context management by giving agents a minimalist interaction model for context, similar to reading and writing files. OpenViking supports hierarchical context loading, semantic retrieval, recursive retrieval, sessions, metrics, and observability, making it possible for AI agents to access the right level of information without stuffing everything into the prompt.
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    oh-my-claudecode

    oh-my-claudecode

    oh-my-claudecode

    oh-my-claudecode is a multi-AI orchestration plugin for Claude Code that helps developers coordinate Claude, Gemini, and Codex in one structured workflow. The platform is designed to turn Claude Code into a more powerful development environment with specialized agents, skills, execution modes, and MCP-powered tools. It includes 19 specialized agents for planning, architecture, debugging, execution, review, security, testing, design, documentation, and other software development tasks. oh-my-claudecode supports powerful modes such as Autopilot, Ralph, Ultrawork, Deep Interview, Team, and Planning to match different coding and project needs. The plugin also includes tools for language server integration, structural code analysis, persistent Python work, project memory, and session state. oh-my-claudecode helps developers automate complex engineering work, coordinate multiple AI systems, and complete coding tasks with more speed and structure.
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    Mem0

    Mem0

    Mem0

    Mem0 is a self-improving memory layer designed for Large Language Model (LLM) applications, enabling personalized AI experiences that save costs and delight users. It remembers user preferences, adapts to individual needs, and continuously improves over time. Key features include enhancing future conversations by building smarter AI that learns from every interaction, reducing LLM costs by up to 80% through intelligent data filtering, delivering more accurate and personalized AI outputs by leveraging historical context, and offering easy integration compatible with platforms like OpenAI and Claude. Mem0 is perfect for projects such as customer support, where chatbots remember past interactions to reduce repetition and speed up resolution times; personal AI companions that recall preferences and past conversations for more meaningful interactions; AI agents that learn from each interaction to become more personalized and effective over time.
    Starting Price: $249 per month
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    Memories.ai

    Memories.ai

    Memories.ai

    Memories.ai builds the foundational visual memory layer for AI, transforming raw video into actionable insights through a suite of AI‑powered agents and APIs. Its Large Visual Memory Model supports unlimited video context, enabling natural‑language queries and automated workflows such as Clip Search to pinpoint relevant scenes, Video to Text for transcription, Video Chat for conversational exploration, and Video Creator and Video Marketer for automated editing and content generation. Tailored modules address security and safety with real‑time threat detection, human re‑identification, slip‑and‑fall alerts, and personnel tracking, while media, marketing, and sports teams benefit from intelligent search, fight‑scene counting, and descriptive analytics. With credit‑based access, no‑code playgrounds, and seamless API integration, Memories.ai outperforms traditional LLMs on video understanding tasks and scales from prototyping to enterprise deployment without context limitations.
    Starting Price: $20 per month
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    Papr

    Papr

    Papr.ai

    Papr is an AI-native memory and context intelligence platform that provides a predictive memory layer combining vector embeddings with a knowledge graph through a single API, enabling AI systems to store, connect, and retrieve context across conversations, documents, and structured data with high precision. It lets developers add production-ready memory to AI agents and apps with minimal code, maintaining context across interactions and powering assistants that remember user history and preferences. Papr supports ingestion of diverse data including chat, documents, PDFs, and tool data, automatically extracting entities and relationships to build a dynamic memory graph that improves retrieval accuracy and anticipates needs via predictive caching, delivering low latency and state-of-the-art retrieval performance. Papr’s hybrid architecture supports natural language search and GraphQL queries, secure multi-tenant access controls, and dual memory types for user personalization.
    Starting Price: $20 per month
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    Constellation Gate AI

    Constellation Gate AI

    Constellation Gate AI

    Constellation Gate AI is a drop-in defense layer for AI agents, built to sit between the agent and the model while screening every request for attacks and leaks. Gate acts as an inline gateway for coding agents and model APIs, protecting workflows without requiring major code changes. Users can point existing tools such as Claude Code, Cursor, OpenClaw, Codex, or OpenCode at Gate and inherit prompt-injection defense, secret scanning, PII redaction, token optimization, and a verifiable audit trail. The platform is designed around three real risks: prompt injection, credential and PII leakage, and hijacked tool calls. Instead of relying on the model to defend itself, Gate blocks attacks before they reach the model, redacts secrets before responses return, and stops attacker-controlled tool outputs before an agent acts on them. Gate accepts the same calls an agent already makes, forwards them to the model, scans every call and response in both directions.
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    Coral

    Coral

    Coral

    Coral is an open-source query layer that allows AI agents and developers to access data across APIs, databases, and file systems using SQL. The platform turns connected sources such as GitHub, Slack, Linear, Datadog, Sentry, Stripe, and PagerDuty into readonly tables that can be explored and joined together. Instead of building custom integrations, ETL pipelines, or API wrappers, teams can use Coral to query multiple systems from one runtime. Coral supports CLI and MCP access, making it usable with tools such as Claude Code, Codex, and other agent frameworks. The platform handles authentication, pagination, rate limits, schema mapping, caching, and semantic hints to improve accuracy and reduce cost. Coral helps engineering teams give AI agents safer, faster, and more useful context for production workflows.
    Starting Price: $249/month
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    MemU

    MemU

    NevaMind AI

    MemU is an intelligent memory layer designed specifically for large language model (LLM) applications, enabling AI companions to remember and organize information efficiently. It functions as an autonomous, evolving file system that links memories into an interconnected knowledge graph, improving accuracy, retrieval speed, and reducing costs. Developers can easily integrate MemU into their LLM apps using SDKs and APIs compatible with OpenAI, Anthropic, Gemini, and other AI platforms. MemU offers enterprise-grade solutions including commercial licenses, custom development, and real-time user behavior analytics. With 24/7 premium support and scalable infrastructure, MemU helps businesses build reliable AI memory features. The platform significantly outperforms competitors in accuracy benchmarks, making it ideal for memory-first AI applications.
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    Engram

    Engram

    Weaviate

    Engram is a fully managed memory and context service purpose-built to help AI agents remember, learn, and improve over time. Instead of treating memory as an ever-growing pile of raw conversations and events, it turns noisy interaction data into structured, durable, and evolving memories. Applications can send raw text, complete conversations, or pre-extracted facts through a REST API or Python SDK without preprocessing. Engram then runs asynchronous pipelines that extract relevant information, transform it by deduplicating and reconciling it with existing knowledge, and commit a clean memory state without blocking the application’s main workflow. It resolves inconsistencies, adapts to changing preferences and time-evolving facts, and keeps context relevant and efficient. Agents can retrieve ranked memories in real time through vector similarity, BM25 keyword search, or hybrid retrieval, reducing the need to resend entire conversation histories.
    Starting Price: $45 per month
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    Memdex

    Memdex

    Memdex

    Memdex turns every AI conversation into reusable local memory by auto-saving chats and bringing the right context back when users need it across ChatGPT, Claude, Gemini, and more. It solves the problem of scattered AI conversations that are hard to find, stuck inside separate tools, and difficult to reuse when starting a new chat. Users can click the Memdex button to save a conversation or turn on auto-save so every AI conversation is captured automatically across supported tools. Memdex then detects relevant context as the user types in any AI tool, highlighting matching words from saved conversations, like spell-check, but for context. When a match appears, users can attach the full previous conversation with one click, allowing the AI to pick up where the earlier discussion left off without re-explaining background, preferences, or project details.
    Starting Price: $7 per month
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    Tuning Engines

    Tuning Engines

    CerebrixOS

    Tuning Engines is a unified AI control and governance layer for teams building production intelligence across models, agents, tools, and fine-tuned systems. It brings together the full AI lifecycle in one governed platform: inference, model routing, fallback policies, fine-tuning jobs, datasets, evaluations, model imports and exports, custom models, agents, MCP servers, reusable skills, guardrails, AGT YAML policies, data capture, runtime traces, usage analytics, API keys, billing, team roles, and integrations. Developers get OpenAI-compatible APIs, Anthropic-compatible routes, CLI workflows, MCP access, coding-agent integrations, and resource catalogs for models, agents, tools, and skills. Teams can connect Claude Code, OpenCode, Aider, Cline, Roo, Continue.dev, Cursor, VS Code, Windsurf, and other AI workflows through a single governed platform.
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    AgentKey

    AgentKey

    AgentKey

    AgentKey connects your AI agents to the world with one key for the external data they need to do real work. Your agent may know what to do, but to actually do it, they need to find the right API, get the right access, and handle every service. AgentKey handles that layer so the agent can search widely, read pages, pull social takes, and add finance, ecommerce, business, crypto, or on-chain context in one pass. Built for Claude Code, Codex, Cursor, Windsurf, Gemini CLI, OpenClaw, Hermes, Antigravity, Warp, and any platform that supports MCP or Skills files, AgentKey gives agents access to search, scraping, social media, finance, ecommerce, cryptocurrency, and business data without forcing users to juggle separate provider dashboards. Search routes include services like Brave Search, Tavily, Serper, Perplexity, Parallel, and Exa, while scraping routes use tools such as Firecrawl, Jina, and Bright Data to turn web pages into usable content.
    Starting Price: $9.90 per month
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    PinAppAI

    PinAppAI

    PinAppAI

    PinAppAI is visual feedback software that turns website change requests into structured tasks for AI coding agents. Reviewers place pins on live website elements and describe changes using plain language or voice input. AI agents like Claude Code and Codex receive localized requests with element identification, text selections, and pixel-perfect captures. The platform supports four pinning modes: free-form pins with percentage-based positioning, element pins for precise HTML targeting, screenshot pins for pixel-perfect images, and text-selection pins for exact find-replace operations. PinAppAI integrates with AI coding tools via Model Context Protocol, letting reviewers annotate live sites while AI agents propose fixes in the editor. It works with Claude Code, Cursor, Continue, Codex, and Claude Desktop. Access options include review links, embedded widgets, a Chrome extension, and a macOS app.
    Starting Price: $9/month/user
  • 38
    Acontext

    Acontext

    MemoDB

    Acontext is a context platform for AI agents. It stores multi-modal messages/artifacts, monitors agents' task status, and runs a Store → Observe → Learn → Act loop that identifies successful execution patterns, so autonomous agents can act smarter and succeed more over time. Developer Benefits: Less Tedious Work: Store multi-modal context and artifacts in one place by integrating all context data without configuring Postgres, S3, or Redis, and it only requires a few lines of code. Acontext handles repetitive, time-consuming configuration tasks, so developers don’t have to. Self-Evolving Agents: Similar to Claude Skills, which require predefined rules, Acontext allows agents to automatically learn from past interactions, reducing the need for constant manual updates and tuning. Easy Deployment: Open-source, one-command setup, One-line install. Ultimate Value: Improve agent success rates and reduce running steps, then save costs.
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    Multilith

    Multilith

    Multilith

    Multilith gives AI coding tools a persistent memory so they understand your entire codebase, architecture decisions, and team conventions from the very first prompt. With a single configuration line, Multilith injects organizational context into every AI interaction using the Model Context Protocol. This eliminates repetitive explanations and ensures AI suggestions align with your actual stack, patterns, and constraints. Architectural decisions, historical refactors, and documented tradeoffs become permanent guardrails rather than forgotten notes. Multilith helps teams onboard faster, reduce mistakes, and maintain consistent code quality across contributors. It works seamlessly with popular AI coding tools while keeping your data secure and fully under your control.
  • 40
    OpenCode

    OpenCode

    Anomaly Innovations

    OpenCode is the AI coding agent purpose-built for the terminal. It delivers a responsive, themeable terminal UI that feels native while streamlining your workflow. With LSP auto-loading, it ensures the right language servers are always available for accurate, context-aware coding support. Developers can spin up multiple AI agents in parallel sessions on the same project, maximizing productivity. Shareable links make it easy to reference, debug, or collaborate across sessions. Supporting Claude Pro and 75+ LLM providers via Models.dev, OpenCode gives you full freedom to choose your coding companion.
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    EverMemOS

    EverMemOS

    EverMind

    EverMemOS is a memory-operating system built to give AI agents continuous, long-term, context-rich memory so they can understand, reason, and evolve over time. It goes beyond traditional “stateless” AI; instead of forgetting past interactions, it uses layered memory extraction, structured knowledge organization, and adaptive retrieval mechanisms to build coherent narratives from scattered interactions, allowing the AI to draw on past conversations, user history, or stored knowledge dynamically. On the benchmark LoCoMo, EverMemOS achieved a reasoning accuracy of 92.3%, outperforming comparable memory-augmented systems. Through its core engine (EverMemModel), the platform supports parametric long-context understanding by leveraging the model’s KV cache, enabling training end-to-end rather than relying solely on retrieval-augmented generation.
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    21st

    21st

    21st.dev

    21st is a developer platform that provides the fastest way to add AI agents directly into applications. The platform offers an SDK that allows developers to define, deploy, and run AI agents with minimal infrastructure setup. Developers can integrate agents using popular frameworks such as Next.js, React, TypeScript, Python, and Node.js. 21st includes built-in features like chat interfaces, session history, tool execution, memory, and real-time streaming responses. The platform also manages backend components such as sandboxed execution environments, authentication, rate limits, and observability. With support for Claude Code and Codex runtimes, developers can build agents that interact with tools, files, and APIs securely. By handling infrastructure and deployment automatically, 21st enables teams to launch production-ready AI agents quickly.
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    ServBay

    ServBay

    ServBay

    ServBay is an AI-native local dev platform for web developers and coding agents, providing a pre-configured web stack alongside local AI infrastructure. 🚀 AI-Native Features: MCP Server: Connect local environments with AI agents (Claude Code, Cursor, Codex). AI can manage sites, change runtimes, and query databases programmatically. (macOS/Windows) Secure AI Gateway: Centralize API keys (OpenAI, Claude, Gemini, local Ollama) into a locally-encrypted endpoint. Track usage and budgets on a unified dashboard. Remote App: Monitor agent tasks, approve execution requests, restart databases, and generate public preview URLs on the go (iOS/Android). 🛠️ Complete Local Stack: 50+ coexisting runtimes (PHP, Node.js, Python, Go, Ruby, Rust, .NET). Databases & Servers: MySQL, PostgreSQL, Redis, MongoDB, NGINX, Apache, and Caddy. Utilities: dnsmasq (DNS), Mailpit (email), and automatic local SSL. Non-intrusive setup: Everything runs in a single folder for easy b
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    Clawd.run

    Clawd.run

    Clawd.run

    Clawd.run is a platform to build and deploy AI agents that can perform real tasks using large language models like Claude, GPT-4, Grok, or Gemini, combining web search, memory, file analysis, and automation into customizable assistants. Users can create agents with defined personalities and purposes, connect them to messaging channels such as Discord, WhatsApp, or the platform’s web chat, and start interacting in minutes without needing extensive infrastructure. Agents on Clawd.run have private data storage, don’t train on your conversations, and remember past interactions to become more helpful over time while offering advanced capabilities like research synthesis, content generation, and data extraction from documents. It provides simple setup steps (name the agent, link the channel, start chatting), supports file uploads for insight extraction, and lets users assign tasks as if the agent were an assistant that can help research, write, code, and analyze.
    Starting Price: $29 per month
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    PrimeClaws

    PrimeClaws

    PrimeClaws.com

    PrimeClaws is a managed hosting platform for OpenClaw autonomous AI agents that lets users deploy and run their OpenClaw instances in the cloud with minimal setup and no DevOps knowledge; it focuses on providing a simple, one-click deployment process so an AI assistant built on OpenClaw can run 24/7 without requiring your laptop or local server to stay on. With support for major LLMs (like Claude, GPT, and Gemini) and persistent memory across sessions, agents can continue working and remembering context over time, and it integrates with messaging channels such as WhatsApp, Telegram, Slack, and others, so your AI assistant can be accessed and interacted with through familiar communication apps. Hosting through ClawHost abstracts infrastructure management, offering global cloud operations with persistent uptime, root access on self-hosted VPS environments, and full control over your agent’s environment, while automatically keeping the AI instance running.
    Starting Price: $9.99/month
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    Maximem

    Maximem

    Maximem

    Maximem is an AI context management and memory platform designed to give generative AI systems a persistent, secure memory layer that retains and organizes information across conversations, applications, and models. Large language models typically operate with limited session memory, meaning they lose context between interactions and require users to repeatedly provide the same background information. Maximem addresses this limitation by creating a private memory vault that stores relevant context, preferences, historical data, and workflow information so AI systems can reference it in future interactions. It operates between AI models and applications, ensuring that conversations, knowledge, and user data are consistently available across different tools and sessions. This persistent memory allows AI assistants to deliver responses that are more personalized, accurate, and context-aware because the system can retrieve previously stored information.
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    Cognee

    Cognee

    Cognee

    ​Cognee is an open source AI memory engine that transforms raw data into structured knowledge graphs, enhancing the accuracy and contextual understanding of AI agents. It supports various data types, including unstructured text, media files, PDFs, and tables, and integrates seamlessly with several data sources. Cognee employs modular ECL pipelines to process and organize data, enabling AI agents to retrieve relevant information efficiently. It is compatible with vector and graph databases and supports LLM frameworks like OpenAI, LlamaIndex, and LangChain. Key features include customizable storage options, RDF-based ontologies for smart data structuring, and the ability to run on-premises, ensuring data privacy and compliance. Cognee's distributed system is scalable, capable of handling large volumes of data, and is designed to reduce AI hallucinations by providing AI agents with a coherent and interconnected data landscape.
    Starting Price: $25 per month
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    Claude Sonnet 4.5
    Claude Sonnet 4.5 is Anthropic’s latest frontier model, designed to excel in long-horizon coding, agentic workflows, and intensive computer use while maintaining safety and alignment. It achieves state-of-the-art performance on the SWE-bench Verified benchmark (for software engineering) and leads on OSWorld (a computer use benchmark), with the ability to sustain focus over 30 hours on complex, multi-step tasks. The model introduces improvements in tool handling, memory management, and context processing, enabling more sophisticated reasoning, better domain understanding (from finance and law to STEM), and deeper code comprehension. It supports context editing and memory tools to sustain long conversations or multi-agent tasks, and allows code execution and file creation within Claude apps. Sonnet 4.5 is deployed at AI Safety Level 3 (ASL-3), with classifiers protecting against inputs or outputs tied to risky domains, and includes mitigations against prompt injection.
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    Cosyra

    Cosyra

    Cosyra

    Cosyra is a mobile-first cloud development environment that enables users to run AI-powered coding tools directly from their phone through a full Linux terminal. It allows developers to use tools such as Claude Code, Codex CLI, OpenCode, and Gemini CLI, all pre-installed and ready to run by simply adding an API key and opening the terminal. It provides an isolated Ubuntu container with essential development tools, including Node.js, Python, Git, tmux, and vim, along with 30 GB of persistent storage that contains data between sessions. Cosyra is designed to replicate the experience of working on a local machine, allowing users to build, test, and manage projects entirely from a mobile device. It supports workflows such as cloning repositories, reviewing pull requests, running tests, and deploying code, all within a persistent session that can hibernate and resume seamlessly.
    Starting Price: $29.99 per month
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    Whim

    Whim

    Whim

    Whim is a cloud dev workspace for running AI coding agents at the speed of thought. It lets developers run AI coding agents like Claude Code and Codex in isolated cloud containers instead of running them locally on a laptop. Each task gets its own sandboxed Ubuntu environment with full shell access, git branch isolation, and real-time terminal streaming, allowing developers and teams to use AI coding agents in daily workflows with parallelism, collaboration, and zero local setup. Users can connect a repo, write a prompt, and the AI agent starts working in a secure cloud container accessible from any device. Multiple tasks can run simultaneously, making it possible to try different approaches, work on separate features, or let an orchestrator coordinate a squad of agents without them stepping on each other’s toes. Whim supports Claude and GPT models through native CLI runtimes, with additional models planned through OpenRouter.
    Starting Price: $50 per month