Alternatives to Markbase

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

  • 1
    EverOS

    EverOS

    EverMind

    EverOS is a persistent memory infrastructure platform for AI agents that provides long-term, multimodal, cross-platform context across agent workflows. The system retrieves relevant memories before model calls, allowing agents to reuse prior context without repeatedly loading large histories into the prompt window. EverOS also includes self-evolving skills, which capture successful execution trajectories as cases and promote recurring patterns into reusable procedural knowledge. The platform can ingest PDFs, images, documents, spreadsheets, slides, Markdown, and URLs and convert them into searchable memory for inference-time retrieval. It supports cloud and self-hosted deployment, exports memories in Markdown, and integrates with tools such as Claude Code, Codex, OpenClaw, Hermes, MCP, and OpenAI- or Anthropic-compatible SDKs. EverOS achieves 93.05% on the LoCoMo long-term memory benchmark (research: arXiv:2601.02163).
    Starting Price: Free
  • 2
    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.
  • 3
    claude-mem

    claude-mem

    cmem.ai

    claude-mem is an offline-first cloud memory for AI agents, built around an open source engine and a cloud sync layer that links agent memory everywhere through one private MCP link. It is designed so coding agents and AI assistants do not start from zero every session, every machine, or every editor. claude-mem takes notes while an agent works, capturing decisions, fixes, dead ends, environment notes, architecture choices, and other structured observations in a temporal database. CMEM Cloud then mirrors that local memory behind a private Model Context Protocol endpoint, allowing any compatible agent or IDE to read and write the same memory across tools such as Claude Code, Cursor, Windsurf, OpenCode, Codex CLI, Gemini CLI, and VS Code. It works locally first, with or without a network, while keeping memory synchronized when cloud access is available.
    Starting Price: Free
  • 4
    past.dev

    past.dev

    past.dev

    past.dev is a long-term memory API for developers building AI agents and applications. Applications send timestamped text from conversations, email, meetings, support records, CRM notes, and documents; the service derives memories and returns ranked results with dates and excerpts from the source data. Its API supports ingestion, batch ingestion, recall, deletion, project and identity management, audience-based access controls, and webhooks. Developers can connect through JSON endpoints or authenticated Model Context Protocol servers, and install companion plugins for Claude Code, Codex, Cursor, JetBrains IDEs, and Hermes Agent. The managed cloud service offers a console for API keys, usage, and request logs; enterprise deployments can run in a customer's AWS, Google Cloud, or Azure account. It is aimed at software teams adding persistent, source-grounded memory to AI agents and other applications.
    Starting Price: $99/month
  • 5
    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.
    Starting Price: Free
  • 6
    SenseLab

    SenseLab

    SenseLab

    SenseLab is a cloud-based memory and learning layer for AI agents and agent-driven applications. It provides shared knowledge spaces (“Rooms”) where agents and teams can record, retrieve, and share context across sessions, models, and tools. Agents can store findings, decision context, and outcomes; the service maintains versioned records and uses outcome feedback to adjust confidence in knowledge. SenseLab provides an MCP server and Python and TypeScript SDKs for connecting agent clients and applications through API-key access. Teams can use it to carry context between agents, coordinate work, review decision histories, and retain structured traces for evaluation or model-training workflows. It is intended for developers and organizations building systems with multiple AI agents. The vendor also documents a self-hosting option through its open-source codebase.
    Starting Price: $29/month
  • 7
    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.
  • 8
    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
  • 9
    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
    Starting Price: $100
  • 10
    Memmy

    Memmy

    Memmy

    Memmy is a local-first AI memory layer that lets every AI tool remember the same version of you. Built for people who work with several assistants every day, it automatically reads authorized collaboration history from tools such as Cursor, Claude, and Codex, then turns scattered conversations, preferences, project context, technical decisions, progress, and recurring pitfalls into structured memory. Its workflow has three stages: Scan reviews selected histories on the user’s device; Organize distills, deduplicates, categorizes, and indexes useful information; and Inject gives the active AI only the most relevant memories through precise, on-demand matching instead of sending a complete data dump. This allows users to switch tools without rebuilding context, merge plans discussed across agents, document recent decisions, preserve writing preferences, and continue unfinished work.
    Starting Price: Free
  • 11
    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
  • 12
    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.
  • 13
    HeyBrain

    HeyBrain

    HeyBrain

    HeyBrain is an AI-powered knowledge management platform that helps organizations centralize company information and make it accessible to employees and AI agents. The platform provides a shared knowledge layer for organizing documents, project context, business decisions, and reusable instructions. Its AI memory capabilities allow compatible AI assistants to retrieve relevant information across conversations and workflows without repeatedly providing the same background. HeyBrain supports document uploads, knowledge connections with Google Drive and Notion, and integration with AI tools through the Model Context Protocol (MCP). Its governance capabilities help organizations manage access to shared information, define agent permissions, and review source evidence behind AI-generated answers. The platform is designed to support enterprise knowledge retrieval, AI agent development, team collaboration, and secure information sharing across business applications.
    Starting Price: $30/month
  • 14
    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
  • 15
    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.
    Starting Price: Free
  • 16
    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.
    Starting Price: Free
  • 17
    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
  • 18
    runx

    runx

    0state

    runx is an open-source runtime and command-line tool for creating, discovering, and executing governed skills for AI agents. Developers can define bounded workflows, grant specific credentials and permissions, and run skills locally with their own provider accounts. Runs can pause for approval or missing input, then resume while retaining a signed receipt that can be inspected and verified. Skills can be installed from a public registry and used with compatible agents such as Claude Code, Cursor, and Codex. An optional hosted service adds managed OAuth connections, scoped grants, API-based run submission and inspection, approval handling, and receipt notarization. The CLI can also operate locally or in a self-hosted environment. runx is intended for developers and platform teams building and operating AI-agent workflows that need explicit authority boundaries and auditable execution.
  • 19
    Campfire SMS

    Campfire SMS

    Campfire SMS

    Campfire SMS is a hosted, two-way SMS bridge for developers who use AI coding agents. It connects an agent running in a local session—or a configured cloud agent—to a verified phone number, sending task updates and questions to the user’s regular text inbox and passing replies back to the agent. The service supports MCP-compatible clients, with setup instructions for Codex, Claude Code, Cursor, Grok Build, OpenCode, and Grok Bot. Local agents require the computer and session to remain active; configured Grok Bot routines can run in the cloud while the computer is off. Users can receive build or test completion notices, respond to agent questions, and guide ongoing coding work away from the desk. SMS delivery uses a hosted account and message credits; the agent’s own model, tools, and task execution remain in the agent environment.
    Starting Price: $5 one-time
  • 20
    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.
    Starting Price: Free
  • 21
    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
  • 22
    scribe

    scribe

    scribe

    scribe is a self-hosted knowledge base written automatically by your tools. It reads Git history, Claude Code and Codex sessions, self-sent URLs, and drop files, then turns that work into a curated, cross-project wiki of plain Markdown stored in Git. Instead of making developers maintain a second brain or rebuild context whenever an agent session starts from zero, scribe captures decisions, fixes, evaluations, and the reasoning behind them so agents can query that memory before they act. Its pipeline runs on cron: it discovers projects, filters low-value noise with FTS5 before invoking an LLM, extracts grounded facts through bounded and two-pass workflows, and compiles them into entity-first pages with YAML frontmatter, wikilinks, backlinks, retrieval context, and typed relationships such as supersedes, contradicts, derived_from, specializes, and extends.
  • 23
    Membase

    Membase

    Unibase

    Membase is a long-term memory service for people and developers building AI agents. It brings information from conversations, files, web pages and connected apps into a persistent memory that users can review, correct, delete and export. A web app and Chrome extension let users manage memories, save browser content and share selected information with supported AI tools. Developers connect custom agents through MCP, the REST API, command-line interface, or Python and TypeScript SDKs. Separate memories and access controls support personal, project and client contexts, with controls to grant or revoke access. The hosted service stores and processes source content to build and retrieve memory.
  • 24
    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
  • 25
    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
  • 26
    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
  • 27
    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.
    Starting Price: Free
  • 28
    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
  • 29
    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.
    Starting Price: Free
  • 30
    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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    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
  • 32
    Flowtask

    Flowtask

    Flowtask

    Flowtask turns Slack messages, emails, and documents into operational memory and accountable work. Every conversation is structured into an executable skills file, so each agent can understand what is open, who owns it, what is blocked, and what happened before without repeated context or manual updates. Its AI Task Builder reads conversations live, extracts requests, deadlines, sender details, attachments, decisions, and thread history, then creates tasks shaped for client deliverables, internal actions, follow-ups, approvals, escalations, or blockers. Smart Assignment routes each task to the right owner using workspace context and rules, while the Priority Engine interprets urgency from tone, service-level agreements, and timelines. Email-to-Task and Slack capture keep work visible without asking teams to change habits, and status synchronization keeps communication and execution aligned.
    Starting Price: $5.23 per month
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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
  • 34
    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.
    Starting Price: Free
  • 35
    StackRails

    StackRails

    StackRails

    StackRails is a software architecture and AI coding governance platform for engineering organizations. It builds a live knowledge graph of repositories, services, APIs, events, and cloud infrastructure, then provides coding agents with architecture and policy context through the Model Context Protocol (MCP). It supports Claude Code, GitHub Copilot, Cursor, and OpenAI Codex, and checks generated code against organization-defined rules on developers’ machines and in pull-request workflows. Teams can use it to map cross-repository dependencies, assess change impact, maintain architecture documentation, manage engineering policies, and run AI-assisted architectural reviews. StackRails is available as a hosted EU service, in customer-managed cloud environments on AWS, Microsoft Azure, or Google Cloud, and as an on-premises deployment.
    Starting Price: $15,000/year
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    Dorchestrator

    Dorchestrator

    Dorchestrator

    Dorchestrator brings Claude Code, OpenAI Codex, and built-in coding agents into one desktop workspace. Plan and review tasks on a Kanban board, coordinate multi-agent swarms, reuse terminal layouts and Skills, and inspect readable tool activity with workflow state stored in your selected project folder.
    Starting Price: $19/month/user
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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.
  • 38
    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
  • 39
    Kuudo

    Kuudo

    Openbridge

    Kuudo is an integration platform that connects AI clients and reusable agent skills to Amazon advertising, seller, and vendor workflows through MCP servers. Teams can analyze campaigns, search terms, product listings, inventory, orders, and profitability using Amazon data processed in their own cloud environment. Kuudo supports Amazon Ads, the Selling Partner API, Vendor Central, and Amazon Marketing Cloud, and works with MCP-compatible clients including Claude, ChatGPT, Codex, Cursor, and Gemini. API access supports custom workflows. The free Community tier includes a monthly API-call allowance, while managed plans use usage-based billing.
    Starting Price: Free; $0.95/1,000 API calls
  • 40
    blume

    blume

    blume

    Blume is a desktop sidecar for AI coding agents that helps developers see what every agent is doing, keep project context consistent, and catch drift before it reaches the codebase. It works with tools including Cursor, Claude Code, Codex, omp, and Pi, bringing agent activity, hidden files, skills, hooks, rules, and provider usage into one place. The Agents view shows whether each coding agent is working, finished, or waiting for approval, while Setup exposes the instructions and configuration files shaping agent behavior. Usage tracking shows remaining plan limits and token burn across providers such as Claude, Codex, and Cursor so developers can avoid unexpected interruptions. Blume stores conversation history locally on the device and reviews rules, skills, and hooks on-device. Its Improve workflow looks for repeated signals of friction across conversations, clusters similar issues, and proposes concrete changes such as new rules or reusable skills.
    Starting Price: Free
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    Agent Teams

    Agent Teams

    MB Skydis

    Agent Teams is a hosted AI-agent workspace for solo founders and early-stage startups. Users can create a lead agent and specialist agents for product, growth, and operations, then coordinate work through shared tasks, files, and messages. Hosted agents can use persistent files and memory, browser access, tools, and schedules to handle ongoing work beyond a single browser session. The shared workspace lets users review agent conversations and activity and collaborate with invited colleagues. Agent Teams supports Hermes and OpenClaw workers, model and tool choices, and connectors for WhatsApp, Telegram, and Slack. Compatible AI clients, including Codex, Cursor, and Claude Code, can connect through supported reporting or MCP tools. The service is designed for startup teams coordinating AI-assisted product, growth, and operational work.
    Starting Price: $199/month
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    OpenChiip Harness
    OpenChiip Harness is a self-hosted AI agent runtime and orchestration framework for developers building local or coordinated agent workflows. It combines LLM conversations, skill orchestration, tool execution, multi-layer memory, resource monitoring, and multi-agent collaboration in a React administration dashboard. Run it as a local service or connect it to the OpenChiip platform for collaborative scheduling. Its CLI, web dashboard, HTTP API, and WebSocket interface support chat, tools, sessions, memory, task management, and monitoring. It supports Baidu ERNIE, OpenAI-compatible model providers, and delegation to Codex or Claude Code. Install via pip or deploy with Docker, Linux packages, systemd, or Windows installers; macOS supports pip installation. Licensed under AIGCGPL-1.0.
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    PostSider

    PostSider

    PostSider

    PostSider is a social media management, scheduling, and publishing platform built for creators, teams, agencies, developers, and AI agents. Manage and schedule content across 30+ social networks from a single calendar, customize posts for each platform, organize publishing queues, collaborate with team members, use approval workflows, and track cross-platform analytics. PostSider also provides a REST API, TypeScript/Node.js SDK, webhooks, and an MCP server that allows AI agents such as ChatGPT, Claude, Codex, Cursor, and other MCP-compatible tools to securely create, schedule, and publish social media content. Features include automated queues, media management, post previews, bulk CSV imports, templates, analytics, AI-assisted post checking and rewriting, multi-user roles, and encrypted social account connections.
    Starting Price: $20/month
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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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    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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    Composio Instant
    Composio Instant is a cloud-based wallet that lets AI agents call paid tools without developers subscribing to each provider or configuring a separate API key for every service. Developers connect Instant to an agent session, choose which tools are available, and use a shared organization balance; charges are recorded in execution logs. Calls draw from that balance at a per-use rate, and new developer organizations receive a one-time $2 starter credit. Available services include web search, data enrichment, scraping, transcription, voice, weather, and document processing. Developers can connect through Composio’s SDKs and MCP-compatible agent clients, including Claude, ChatGPT, Codex, Cursor, Gemini CLI, Grok, and Visual Studio Code. Instant is intended for developers and teams building or operating AI agents that need on-demand access to external capabilities.
    Starting Price: $29/month
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    ADE

    ADE

    ADE

    ADE is an agentic development environment for software developers who use AI coding agents with Git repositories. It organizes parallel tasks in isolated Git worktrees and combines agent chat, multi-agent sessions, terminals, file editing, testing, browser-based QA, automation, and pull-request review in one workspace. Desktop, browser, terminal, and iOS clients sync project activity through an ADE Brain running on a machine you control; Linux can host the Brain without a Linux desktop app. ADE supports Claude Code, Codex, Cursor, Factory Droid, and OpenCode, and connects to GitHub and Linear for pull requests and issue workflows. Developers can review changes, inspect test results, and continue work across devices.
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    Weaviate

    Weaviate

    Weaviate

    Weaviate is an open-source, AI-native vector database for building search, RAG, and agentic AI applications. Store data objects alongside vector embeddings from your favorite ML models and scale seamlessly into billions of objects. Bring your own vectors or use built-in vectorization, then combine vector, keyword, and hybrid search for state-of-the-art results, even with filters. Pipe results through leading LLMs to power next-generation, retrieval-augmented experiences. Weaviate goes beyond the database: the Query Agent turns natural language into precise, cited queries, Engram provides managed memory for AI agents, and Weaviate Embeddings handles vectorization for you. Run it yourself under an open-source license, or use fully managed Weaviate Cloud on AWS, GCP, or Azure, with SOC 2 Type II compliance, multi-tenancy, and RBAC built in. Use any generative model with your own data to build chatbots, semantic search, recommendation, and agentic workflows.
    Starting Price: Free
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    Orca

    Orca

    Stably AI

    Orca is a desktop environment for developers coordinating AI coding agents across software projects. It organizes work in isolated Git worktrees, allowing agents to tackle separate tasks or try the same task in parallel. Each workspace combines an agent terminal with code editing, browser access, and tools to inspect diffs, review changes, and commit or push work. Orca supports command-line agents such as Claude Code, Codex, Cursor CLI, and OpenCode, and can connect work to code repositories and issue-tracking tools. Developers can run agents locally or on remote machines, organize work into sessions, and use a mobile companion to monitor sessions away from the desktop. A command-line interface supports workspace and agent-task automation. Orca is designed for developers working with code and Git who want to supervise multiple AI-assisted coding tasks; it is a desktop application rather than a hosted coding service.
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    AgentPass.ai

    AgentPass.ai

    AgentPass.ai

    AgentPass.ai is a secure platform designed to facilitate the deployment of AI agents in enterprise environments by providing production-ready Model Context Protocol (MCP) servers. It allows users to set up fully hosted MCP servers without the need for coding, incorporating built-in features such as user authentication, authorization, and access control. Developers can convert OpenAPI specifications into MCP-compatible tool definitions, enabling the management of complex API ecosystems through nested structures. AgentPass.ai also offers observability features like analytics, audit logs, and performance monitoring, and supports multi-tenant architecture for managing multiple environments. By utilizing AgentPass.ai, organizations can safely scale AI automation while maintaining centralized oversight and compliance across their AI agent deployments.
    Starting Price: $99 per month