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  1. Home/
  2. evermemos-mcp/
  3. Alternatives

evermemos-mcp Alternatives

evermemos-mcp is an open-source Model Context Protocol (MCP) server that brings long-term memory capabilities to AI coding tools through integration with EverMemOS. Below are 21 frameworks & sdks apps with similar functionality to evermemos-mcp, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.

  • mnemo-mcp
    github.com

    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.

  • memanto-mcp
    pypi.org

    Memanto is an open-source, on-premises memory agent designed to provide persistent semantic memory for AI agents. It addresses the challenge of enabling AI agents to retain, organize, and recall information across sessions, helping them avoid forgetting decisions, conventions, and context between interactions. The tool is built on an information-theoretic search engine and is structured to run entirely on a user's local machine, requiring no API keys, vector databases, or external backend services. Memanto supports instant ingestion of information, with memories becoming searchable immediately after being written, and boasts recall latency of under 90 milliseconds. It implements features such as conflict resolution, semantic categorization into 13 types, verifiable memory sources, deterministic search, temporal queries, and info-theoretic scoring. The system is designed to prioritize freshness, ensuring that new facts outrank outdated ones, and automatically resolves conflicting data as it is ingested. The platform offers a range of integrations, supporting over 17 different agents and frameworks, including Claude Code, Cursor, Codex, GitHub Copilot, Gemini, and others. Users can manage agents, store memories, and perform retrieval-augmented generation (RAG) directly from the command line interface. Additionally, Memanto provides a local interactive dashboard for managing agents and memories, viewing conflicts and connections, and migrating from other memory solutions. Embeddings and answers are processed locally, ensuring that no data leaves the user's laptop. Installation is streamlined through a single pip install command, and users can choose between cloud and on-premises backends, with the on-premises option requiring Docker and running on localhost. Memanto is positioned as a solution for developers and teams building or operating AI agents who require reliable, persistent, and private memory infrastructure. The tool is offered completely free of charge under an open-source license.

  • projectmind-mcp
    pypi.org

    projectmind-mcp is an open-source local MCP server that equips AI coding assistants with persistent memory, hybrid code search, AI-generated annotations, and an AST symbol graph. It runs entirely locally, requiring no API keys, and is aimed at developers seeking privacy and advanced code intelligence features.

  • personal-memory-mcp
    pypi.org

    personal-memory-mcp is an open-source CLI tool that runs a local MCP server to extract and store personal memory from AI chat histories. It is intended for users and developers who want to manage their AI interaction data locally and securely.

  • mcp-external-memory
    pypi.org

    mcp-external-memory is an open-source MCP server that provides large language models with persistent and searchable semantic memory. It enables AI developers to enhance LLM capabilities by integrating long-term memory and efficient retrieval into their applications.

  • codebase-memory-mcp
    pypi.org

    codebase-memory-mcp is an open-source, fast code intelligence engine designed for AI coding agents. Distributed as a single static binary MCP server, it enables local analysis of codebases for agent frameworks and research. It is suitable for developers building AI-powered code tools and workflows.

  • thought-mcp
    github.com

    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.

  • AutoMem
    automem.ai

    AutoMem is an open-source infrastructure tool that provides persistent memory for AI agents via MCP and HTTP interfaces. It supports both local and cloud deployments, enabling agents to store and recall structured and semantic data efficiently.

  • devmemory-ai
    pypi.org

    devmemory-ai is an open-source persistent MCP server designed to provide cross-tool coding context and developer memory. It enables developers to maintain context across different tools and sessions, improving productivity and workflow integration.

  • memory-bridge-mcp
    pypi.org

    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.

  • memory-quality-mcp
    github.com

    A Claude Code MCP plugin that audits and cleans up your AI memory store

  • supermem
    pypi.org

    supermem is an open-source command-line tool that provides persistent AI memory using a four-tier retrieval system, integrating SQLite FTS5, graph, vector, and LLM agent layers. It is designed for AI developers and researchers seeking advanced memory and retrieval capabilities for language models.

  • memosq
    pypi.org

    memosq is an open-source framework that provides persistent, cross-agent memory for AI coding assistants. It leverages semantic search and SQLite to store and retrieve contextual information, enabling more effective and context-aware AI agent collaboration.

  • ithz-mcp
    pypi.org

    ithz-mcp is an open-source library that offers local-first, deterministic project memory for AI coding agents and Model Context Protocol workflows. It is designed for developers building autonomous agent systems and coding assistants.

  • ai-dememory
    pypi.org

    ai-dememory is an open-source toolchain and MCP server that enables AI agents to store, manage, and retrieve memory locally across multiple large language models. It is designed for developers building personal or autonomous AI systems that require persistent, local-first memory infrastructure.

  • second-brain-mcp
    pypi.org

    second-brain-mcp is an open-source MCP server that transforms an Obsidian vault into a semantic memory resource for coding agents. It enables retrieval-augmented generation and memory for agent frameworks, supporting local deployment and integration with Obsidian.

  • Recall
    recallmcp.com

    Recall is an infrastructure service that provides persistent, cross-session memory and semantic search for AI agents. It supports the MCP protocol, multi-tenant isolation, and real-time collaboration, enabling developers to build agents with long-term knowledge retention and context sharing.

  • mcp-ai-forever
    github.com

    Enhanced MCP server for interactive user feedback and command execution in AI-assisted development, featuring dual interface support (Web UI and Desktop Application) with intelligent environment detection and cross-platform compatibility.

  • contextl-mcp
    pypi.org

    contextl-mcp is an open-source MCP server designed for AI coding agents. It provides repository intelligence, code search, and integrates with the Model Context Protocol, allowing developers to build advanced AI-powered code tools. Distributed under the MIT license.

  • MemBrain
    mem-brain.io

    MemBrain is an infrastructure platform that provides persistent, self-evolving memory for AI agents. It enables developers to store, traverse, and recall knowledge graphs and reasoning paths via API or CLI, supporting integration with any LLM through MCP or REST.

  • Claude-mem
    claude-mem.ai

    claude-mem and cmem are open-source tools that provide persistent memory and Model Context Protocol (MCP) integration for AI agents. They enable agents to retain, sync, and recall context across sessions, supporting both local and cloud deployments for developers building advanced agent frameworks.