Best Agentic AI Platforms - Page 17
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Junction
Junction
Junction Panel is a lightweight control surface for managing AI coding agents from anywhere, designed to keep developers connected to their workflows without being tied to a desktop environment. It enables users to monitor, interact with, and control multiple local AI agents in real time, receiving alerts when an agent needs input and responding instantly from any device, including a phone. Through a unified interface, users can review diffs, tail logs, merge pull requests, and approve execution steps with one-tap actions, allowing development processes to continue seamlessly even when away from a workstation. It includes built-in features such as per-turn cost tracking for token usage, workspace browsing, custom commands, and agent checkpoints that allow rollback to previous states if something goes wrong. It also introduces a structured permission system with five levels of risk classification, ensuring that every agent action is categorized and reviewed appropriately.Starting Price: $10 per month -
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A2UI
A2UI
A2UI is a declarative UI protocol designed to enable AI agents to generate rich, interactive user interfaces that render natively across web, mobile, and desktop environments without executing arbitrary code. Instead of relying on text-only interactions or unsafe approaches like sending HTML or JavaScript, A2UI allows agents to communicate UI intent through structured JSON messages that describe components, layouts, and data bindings, which client applications then render using their own trusted, pre-approved components. This approach separates UI generation from UI execution, ensuring that interfaces are secure, consistent with the host application’s design system, and adaptable across platforms. It is designed to be LLM-friendly, using a flat, streaming JSON structure that allows agents to incrementally build and update interfaces in real time, enabling progressive rendering and responsive user experiences.Starting Price: Free -
3
Agentspan
Agentspan
Agentspan is an open source server and SDK designed to bring durable execution to AI agents, transforming how they run in real-world environments beyond simple demos. It allows developers to define agents in Python and compile them into persistent, crash-safe workflows where execution state lives on the server rather than in the local process, ensuring that work is never lost if a system crashes or restarts. This architecture enables agents to pause, resume, and continue from the exact step they left off, even when reconnected from a different machine. It supports human-in-the-loop workflows, allowing agents to halt for approval and resume seamlessly through interfaces like Slack, web portals, or code. It also enables multi-agent pipelines, where several agents can be chained together in a single expression, with each step logged, observable, and recoverable across the entire workflow.Starting Price: Free -
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Artyfacts
Artyfacts
Artyfacts is a persistent workspace platform designed for AI agents, enabling their outputs to exist beyond temporary chat interactions and become structured, reusable assets such as research, specifications, reports, and documentation. It addresses a core limitation of current AI workflows, where generated content is often lost or fragmented across chat logs, by providing a centralized environment where work produced by agents can be stored, organized, and iterated over time. It supports outputs from multiple AI systems, including tools like Claude, OpenClaw, or other agents, allowing teams to unify their workflows regardless of the underlying model. Rather than treating AI interactions as disposable conversations, Artyfacts turns them into durable artifacts that can be referenced, edited, and built upon, improving continuity and collaboration in complex projects. It functions as a workspace layer for agent-driven development and research.Starting Price: $7 per month -
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Worktale
Worktale
Worktale is a local-first developer tool that transforms git history into a structured, persistent record of everything a developer builds, combining code activity tracking with AI usage insights in a single system. It operates primarily as a lightweight CLI with an optional desktop interface, scanning repositories to generate a complete work journal based on commit metadata such as timestamps, messages, and line changes, without ever accessing source code. It automatically captures development activity through a post-commit hook or batch import, compiling daily digests that summarize progress, decisions, and output, which can be edited and reused for status updates, performance reviews, or documentation. It includes visual dashboards with streak tracking, contribution heatmaps, and historical analytics, allowing developers to understand productivity patterns over time.Starting Price: $9 per month -
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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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Cofounder
The General Intelligence Company Of New York
Cofounder 2 is an AI automation system designed to help users run and organize workflows across their entire tech stack using natural language as the primary interface. It connects directly to existing tools and platforms, allowing users to automate tasks, manage operations, and coordinate processes without needing to manually configure complex integrations. It uses AI agents that can understand instructions written in plain English, then plan and execute multi-step workflows such as project management, communication handling, or data processing, effectively acting as an intelligent operational layer on top of the software users already rely on. Cofounder emphasizes seamless integration and workflow orchestration, enabling users to link multiple tools together and create automated “flows” that operate across systems. Its agents are capable of reasoning through tasks, adapting to different contexts, and handling technical execution behind the scenes.Starting Price: $20 per month -
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HiClaw
AgentScope
HiClaw is an open source multi-agent OS powered by Matrix. It lets multiple AI agents collaborate in Matrix rooms, fully visible to humans, with real-time intervention capability. A Manager Agent coordinates multiple Worker Agents to complete complex tasks, intelligently decomposing work and enabling parallel execution for stronger complex task handling. Built for enterprise-grade security and multi-agent collaboration, HiClaw uses the open Matrix IM protocol so all agent communications remain transparent, auditable, and suitable for distributed deployment and federation. Humans can enter any Matrix room at any time to observe agent conversations, intervene, or correct agent behavior in real time, ensuring safety and control. It's clear that a two-tier Manager-Worker architecture gives each agent distinct responsibilities and makes it easier to extend the system with custom Worker Agents for different scenarios.Starting Price: Free -
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AG-UI
AG-UI
AG-UI is an open, lightweight, event-based protocol that standardizes how AI agents connect to user-facing applications. Built for simplicity and flexibility, it enables seamless integration between AI agents, real-time user context, and user interfaces. AG-UI is designed for agent-human interaction: during agent executions, backends emit events compatible with standard AG-UI event types, and agent backends can accept simple AG-UI-compatible inputs as arguments. It works with any event transport, including SSE, WebSockets, webhooks, and other streaming systems, while providing a flexible middleware layer that ensures compatibility across diverse environments. AG-UI brings agents into user-facing applications and complements the wider agentic protocol stack: MCP gives agents tools, A2A allows agents to communicate with other agents, and AG-UI connects agents directly to the user interface.Starting Price: Free -
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assistant-ui
assistant-ui
assistant-ui is an open source React toolkit for production AI chat experiences, designed to bring the UX of ChatGPT into your own app. It helps developers create beautiful, enterprise-grade AI chat interfaces in minutes for React, React Native, and terminal applications. Whether you are building a ChatGPT clone, a customer support chatbot, an AI assistant, or a complex multi-agent application, assistant-ui provides frontend primitive components and state management layers so you can focus on what makes your application unique. It includes instant chat UI with pre-built, beautiful, customizable chat interfaces out of the box, making it easy to quickly iterate on an idea. Its chat state management is optimized for streaming responses, interruptions, retries, multi-turn conversations, and efficient rendering. assistant-ui is built for high performance, with optimized rendering and a minimal bundle size to keep AI chat interfaces responsive.Starting Price: $50 per month -
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Kanwas
Kanwas
Kanwas is your team’s context brain: one place for teams and agents to create, edit, share, and compound product context. Instead of juggling Claude chats, local folders, Obsidian, VS Code, Git, and docs, Kanwas gives product teams a shared workspace where context stays alive. It is not just answers, not just outputs, and not starting from scratch; it is a place to think, collaborate, and get sharp deliverables. Kanwas builds shared context by learning about you, your business, and your decisions, making evidence, ideas, and trade-offs transparent to everyone. Canvas plus shared context creates alignment, letting teams and agents work over the same context while generating structured, execution-ready deliverables for every stage of implementation. Every decision and outcome makes the next thinking process and deliverable better than the last, turning stored knowledge into a living board that teams can think in. Kanwas includes a canvas for real work, bringing code, docs, tasks, etc.Starting Price: Free -
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Plurai
Plurai
Plurai is the real-world trust platform for AI agents, built for simulation-driven evaluation, protection, and optimization that turns agents into trusted, continuously improving production systems. It helps teams train evals and guardrails tailored to their use case, bridging the gap from prototype to reliable production at scale. Plurai’s simulation platform prepares agents for the real world, not the lab, with hyper-realistic, product-tailored experimentation and evaluation that covers production complexity. It generates authentic multi-turn scenarios, personas, required artifacts, and tool mocking, using organizational PRDs, relevant sources, and policies to build a knowledge graph and expand edge-case coverage. Instead of relying on static datasets, manual test creation, or inconsistent LLM-as-a-judge methods, Plurai groups evaluations into structured, runnable experiments so teams can test new versions, measure regressions, and validate improvements before release.Starting Price: Free -
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pay.sh
pay.sh
pay.sh is a pay-per-use API access for agents and command lines, built to let agents pay for any API with one line. It gives agents a normal tool path for paid APIs: discover a service, review the cost, make the request, and receive the response, with no sign-up, no account, and no subscription required. pay.sh is designed for the agentic economy, where autonomous agents need APIs, but today’s best services still demand a human to create an account, choose a plan, add an API key, and attach a credit card. Instead, pay.sh closes that gap with API calls that agents can discover, price, and call directly. It includes a directory for agents, developers, and API teams, helping API providers publish services in a format that agents can inspect and use without asking a human to create an account first. Agents can search the catalog, inspect endpoints, and call pay-per-use services across categories like AI/ML, maps, data, search, messaging, compute, storage, and crypto/finance.Starting Price: Free -
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Agent Control
Agent Control
Agent Control is the open source control plane for AI agents, built to establish a new standard for governing agent behavior at scale. It solves the problem of scattered, hardcoded checks by giving teams a centralized governance layer with step-level enforcement that can be managed from a single control plane and updated in real time without touching agent code. Developers can make any function governable by adding the control() decorator, turning meaningful decision points inside an agent into independently governed control points with their own policies. When a decorated function executes, Agent Control evaluates the input or output against the active policy and returns a decision: deny, steer, warn, log, or allow. If the decision is denied, the SDK raises a ControlViolationError before the unsafe action can proceed. Policies are decoupled from code, so developers decide where to place control hooks while policy teams decide what those hooks enforce.Starting Price: Free -
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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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Nagent AI
Nagent AI
Nagent AI is an enterprise AI agent platform that helps teams stop building AI tools and deploy agentic applications that execute real business workflows autonomously. Nagent lets anyone, from product managers to customer success teams, create, deploy, and orchestrate AI agents that learn, remember, and act. Its no-code Agent Builder Studio brings models, tools, logic, knowledge, memory, multimodal capabilities, and enterprise-grade safety into one workspace, making it possible to build agents from scratch, customize templates, or ask the AI assistant to help finish parts of the workflow. It includes a proprietary multi-agentic workflow system that orchestrates many agents into one flow, connecting content, research, reporting, and other enterprise processes. Nagent supports 40+ AI models in one platform, allowing users to use one or multiple models without managing separate keys, accounts, or billing.Starting Price: $49 per month -
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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 -
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Proof
Every
Proof is an agent-first document editor built for agents and humans to collaborate. It gives teams a shared document where humans and AI can write together, suggest edits, leave comments, and track who wrote what. Every character carries provenance, with a colored gutter showing authorship, so users can distinguish human-written text from AI-written text. When an AI edits a document, Proof creates suggestions like track changes, with insertions and deletions that users can accept or reject one by one. AI agents can also comment on specific text to explain reasoning, ask questions, flag issues, or continue a conversation inside the document. Users can create a document, share the link with agents such as Claude Code, ChatGPT, Codex, or OpenClaw, and collaborate through a shareable workspace instead of passing around .md files. Proof supports use cases such as bug reports, PRDs, implementation plans, research briefs, growth reports, copy audits, strategy docs, memos, proposals, etc.Starting Price: Free -
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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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Dock
Dock
Dock is the AI workspace for you, your team, and every agent you run. It gives humans and AI agents the same shared cloud workspace, where everyone can read and write the same state in real time instead of working across scattered chats, files, and one-off outputs. Dock is built around tables with typed columns, rich-text docs, and agents as first-class identities, each with their own API keys, permissions, and audit trail rather than delegated human tokens. Teams can use Dock to plan, research, decide, and ship with humans and AI on the same surface, with use cases across engineering, go-to-market, research, operations, solo work, and agency workflows. Engineering teams can manage sprint planning, spec docs, and incident response; GTM teams can organize content calendars, sales pipelines, and customer success; research teams can track interviews, themes, and competitive intelligence; and operations teams can manage runbooks, recruiting, compliance, and onboarding.Starting Price: $19 per month -
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AG2
AG2
AG2 is the open source AgentOS for building production-ready AI agents and multi-agent systems in minutes, not months. Formerly AutoGen, it provides an open source Python framework for building, orchestrating, and scaling AI agents that can collaborate through shared context, use tools, execute workflows, and support both autonomous and human-in-the-loop patterns. AG2 is designed for developers who want to build systems, not prompts, with simple and intuitive syntax, built-in conversation patterns, and a flexible platform for multi-agent automation. Agents in AG2 can extend their capabilities with tools, allowing them to interact with external systems, fetch real-time data, execute code, search the web, process documents, and complete complex tasks beyond a model’s internal knowledge. It supports many LLM providers and local models, including OpenAI-compatible endpoints, Anthropic Claude, Gemini through Vertex AI, DeepSeek, and LM Studio.Starting Price: Free -
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Multica
Multica
Multica is an open source project management platform for human and agent teams, built to turn coding agents into real teammates rather than separate tools. It gives humans and AI agents the same workspace, where agents can be assigned issues, report progress, reply in comments, raise blockers, ship code, and appear in the member list with profiles, avatars, and open-issue queues. Users can assign work to an agent the same way they would hand a task to a teammate, or open a chat window to ask it to draft an issue, answer a question, or handle a one-off request. Multica’s shared context layer keeps issue comments, attachments, reports, task history, and workspace knowledge accessible to both people and agents, while skills act as workspace-wide playbooks that let every agent reuse the same definitions and operating instructions.Starting Price: Free -
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AionUi
AionUi
AionUi is a desktop workspace where AI agents live on the user’s computer and actually collaborate across everyday tasks such as writing code, making slides, sorting files, crunching numbers, editing photos, creating reports, writing papers, and running automations 24/7. Users can work with one agent, run multiple agents in parallel, assign tasks to the right assistant, or team them up inside one unified workspace. AionUi auto-detects Claude Code, Codex, Gemini CLI, Aion CLI, OpenCode, OpenClaw, Goose, and 20+ more tools already installed on the machine, so users can reuse their existing setup without reinstalling or duplicating tools. It includes 20+ built-in assistants for presentations, Excel, financial models, documents, academic papers, diagrams, UI/UX design, games, creative writing, project planning, recruiting, setup, and autonomous end-to-end work. Users can also create custom assistants tailored to their workflow.Starting Price: Free -
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Tulsk
Tulsk
Tulsk is an agentic project management workspace for small startup teams, built to plan, run, and monitor autonomous AI work across projects, docs, tasks, comments, and agent workflows in one shared workspace. Teams use Tulsk to delegate real work to AI agents instead of managing separate chat windows, prompts, and half-finished outputs. Users can mention an agent in any task, and the agent reads the context, executes the work, and posts the result back in the thread with no copy-paste or babysitting. Tulsk combines projects, statuses, priorities, attachments, real-time comments, OpenClaw agent runtime, EMA AI project manager, Skills, MCP access, and agent scheduling in one workspace. OpenClaw gives agents their own dedicated cloud workspace with browser, shell, web search, editable persona files, attached skills, and tool access, so they can handle long-running jobs such as market research, competitor analysis, reports, content drafts, operational checks, and specialized workflows.Starting Price: $39 per month -
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Agent Client Protocol (ACP)
Agent Client Protocol (ACP)
The Agent Client Protocol (ACP) standardizes communication between code editors, IDEs, and coding agents, making agent-editor interoperability the default instead of requiring custom integrations for every possible combination. It provides a standard interface for communication between AI agents and client applications, with a flexible, extensible, and platform-agnostic architecture designed for both local and remote scenarios. ACP addresses integration overhead, limited compatibility, and developer lock-in by allowing agents that implement the protocol to work with any compatible editor, while editors that support ACP gain access to the broader ecosystem of ACP-compatible agents. Similar in spirit to how the Language Server Protocol standardized language server integration, ACP decouples agents and editors so both sides can innovate independently while developers choose the best tools for their workflow.Starting Price: Free -
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Project Solara
Microsoft
Project Solara is Microsoft’s early chip-to-cloud platform for agent-first devices, built to support a future where agents are easy to reach, naturally engaged, and always available across new device form factors. Instead of centering the experience around traditional apps, Project Solara is designed for an open, multi-agent world where specialized agents can be built, deployed, and experienced across every layer of the stack. Microsoft imagines a diverse ecosystem of agent-first devices, from small to large, fixed to hypermobile, and personal to professional, each supported by a base OS, shell, developer ecosystem, apps, web-based intermediation, and silicon integration. It is designed to make agents more capable and accessible by composing hardware, software, cloud services, and developer tools into a foundation for new interaction patterns. Project Solara includes two concept devices that show how agent-first computing could work in practice.Starting Price: Free -
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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 -
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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 -
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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 -
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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
