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MCP 服务器/tomschell mcp long term memory

System · MODEL CONTEXT PROTOCOL

tomschell mcp long term memory

A long-term memory storage system for LLMs using the Model Context Protocol (MCP) standard. This system helps LLMs remember the context of work done over the entire history of a project, even across multiple sessions. It uses semantic search with embeddings to provide relevant context from past interactions and development decisions.

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WHAT IT CONNECTS

tomschell mcp long term memory 为 AI Agent 提供什么

  • Project-based memory organization
  • Semantic search using Ollama embeddings (nomic-embed-text model, 768 dimensions)
  • Multiple memory types:
  • Conversations: Dialog context and important discussions
  • Code: Implementation details and changes
  • Decisions: Key architectural and design choices
  • References: Links to external resources and documentation
  • Rich metadata storage including:
  • Implementation status
  • Key decisions
  • Files created/modified
  • Code changes
  • Dependencies added
  • Tagging system for memory organization
  • Relationship tracking between memories
  • Node.js (v18 or later)
  • Ollama running locally (for embeddings)
  • Must have the `nomic-embed-text` model installed
  • SQLite3
  • Clone the repository
  • Install dependencies:
  • Build the project:
  • Create a `.env` file with required configuration:
  • Start the server in development mode:
  • Compile TypeScript
  • Copy schema files
  • Start the server with auto-reload
  • The server connects via stdio for Cursor compatibility
  • `projects`: Project information and metadata
  • `memories`: Memory entries storing various types of development context
  • `embeddings`: Vector embeddings (768d) for semantic search capabilities
  • `tags`: Memory organization tags
  • `memory_tags`: Many-to-many relationships between memories and tags
  • `memory_relationships`: Directed relationships between memory entries
  • `store-dev-memory`: Create new development memories with:
  • Content
  • Type (conversation/claude-code/decision/reference)
  • Tags
  • Code changes
  • Files created/modified
  • Key decisions
  • Implementation status
  • `list-dev-memories`: List existing memories with optional tag filtering
  • `get-dev-memory`: Retrieve specific memory by ID
  • `search`: Semantic search across memories using embeddings
  • Kill any existing server instances
  • Rebuild the TypeScript code
  • Copy the schema.sql to the dist directory
  • Start the server in development mode
  • `@modelcontextprotocol/sdk@^1.7.0`: MCP protocol implementation
  • `better-sqlite3@^9.4.3`: SQLite database interface
  • `node-fetch@^3.3.2`: HTTP client for Ollama API
  • `zod@^3.22.4`: Runtime type checking and validation
  • Write clear commit messages
  • Add appropriate documentation
  • Follow the existing code style
  • Add/update tests as needed

SECURITY

MCP 收录不等于安全审核

MCP 服务器可能获得模型上下文、凭据、本地文件或调用外部系统的权限。连接 Agent 前，请检查代码、环境变量、网络行为、软件包来源与维护状态。