baton-mcp Alternatives

memory-bridge-mcp is an open-source Python package that provides a unified MCP memory server, bridging Mind (concept graph) and Honcho (semantic vector) memory systems. It supports episodic timelines and LLM synthesis, enabling agent framework developers to manage and integrate multiple memory types in their AI agents.

agent-brain-ag-mcp is an open-source Model Context Protocol (MCP) server that exposes Agent Brain as MCP tools, resources, and prompts. It enables developers to integrate Agent Brain capabilities into agent-based applications, supporting RAG workflows and Claude integration. Ideal for AI developers seeking extensible agent frameworks.

cambium-mcp is an open-source Python package that implements the Model Context Protocol (MCP) for managing the lifecycle of knowledge events. It enables distillation and recall of agent and context-keeper events across projects, supporting local, team, and organizational memory workflows. Designed for developers building AI agent systems.

mcp-brain is a command-line and MCP server framework for multi-agent cognitive processing. It enables developers and researchers to coordinate and execute complex agent-based workflows, supporting advanced automation and distributed AI tasks.

mcp-agent-handoff is an open source portable MCP server designed for managing agent handoff states and review tracking in AI agent workflows. It implements the MCP protocol and can be self-hosted for integration into agentic systems.

MCP server that wraps the basecamp CLI.

thought-mcp is an open-source toolkit that implements a local Model Context Protocol (MCP) memory server with bi-temporal graph, vector, and temporal layers. It enables AI agents to store, retrieve, and consolidate structured memory for advanced reasoning and context management.

agentsync-mcp is an open-source Python package for decentralized coordination among AI agents. It enables agents to claim work, survey peers, detect conflicts, and reconcile changes using the Model Context Protocol (MCP) and git branch operations. Ideal for developers building distributed agent systems.

compos-mcp is an open-source MCP server designed for integrating Compos architectural memory into AI and LLM workflows. It provides a model context protocol implementation, allowing developers to manage and serve contextual memory for advanced AI applications. Suitable for AI developers and researchers building memory-augmented systems.

MCP server for Link local agent memory — remember, recall, search, context, and graph traversal

central-mcp is an open-source Python package that serves as an agent-agnostic MCP hub for managing and orchestrating multiple coding agents. It enables AI developers to coordinate various coding agents using the Model Context Protocol (MCP).

Memanto is a memory agent for AI systems that keeps information available across sessions. It is described as persistent memory for Claude Code, Cursor, Codex, and 14+ other agents, and as a companion memory agent that helps agents focus while the user keeps ownership of what they learn. The product is built on what it calls an information-theoretic search engine. Its core functions include instant ingestion, conflict resolution, verifiable sources, deterministic search, temporal queries, freshness prioritization, and semantic categorization into 13 types. The page says memories become searchable immediately after they are written and reports under 90 ms recall latency. It also says the system supports built-in RAG, confidence scoring, local embeddings, autonomous categorization, and daily summaries. A comparison section states that it supports remember, recall, and answer, and that it returns relevant results rather than dumping everything into context. Memanto is presented as working with agents and frameworks across a broad stack. Named integrations include Claude Code, Cursor, Codex, GitHub Copilot, Gemini, OpenAI Codex CLI, Cline, Windsurf, Continue, opencode, Goose, Roo Code, Augment Code, Hermes Agent, CrewAI, LangChain, LangGraph, LlamaIndex, and n8n. The page also mentions REST and MCP, and it shows a CLI with commands such as memanto connect claude-code and memanto ui. A local interactive dashboard is available for managing agents and memories, viewing conflicts and connections, and migrating from Mem0, Letta, and more. The product is 100% free, open source, and runs entirely on the user’s machine. Installation is shown through pip install memanto, with an on-prem backend using Docker and localhost:8080, and a cloud option that uses an API key. The page also says embeddings and answers can run via local Ollama models, and that no API keys, vector database, or backend service are required for the on-machine setup.

mnemo-mcp is an open-source MCP server that provides persistent memory and embedded synchronization for AI agents. It is designed for developers building agentic systems requiring long-term memory and context management.