anytype-mcp

# Anytype MCP Server A Model Context Protocol (MCP) server for Anytype that enables semantic search and RAG (Retrieval-Augmented Generation) capabilities over your Anytype documents. ## Features - Semantic search across your Anytype documents - Automatic chunking of documents for improved search accuracy - Full metadata support including tags, dates, and custom properties ## Prerequisites - Python 3.13 or higher - [uv](https://github.com/astral-sh/uv) - Modern Python package installer - [Ollama](https://ollama.ai) - For running the embedding model locally - [Anytype](https://anytype.io) desktop application ## Installation 1. Clone the repository: ```bash git clone https://github.com/wethegreenpeople/anytype-mcp.git cd anytype-mcp ``` 2. Install dependencies: ```bash uv sync ``` 3. Install the mxbai-embed-large model with Ollama: ```bash ollama pull mxbai-embed-large ``` 4. Optional: Run initial document ingestion (this can be done later from the client, but depending on your machine and how many notes you have, this might take a few minutes): ```bash python scripts/ingest_only.py ``` 5. Optional: Install the server in Claude: ```bash fastmcp install server.py ``` ## Manual Configuration for Claude Desktop If you want to manually add the Anytype MCP server to your Claude Desktop application, you'll need to modify the `claude_desktop_config.json` file. This file is typically located at: - Windows: `%APPDATA%\Claude\claude_desktop_config.json` - macOS: `~/Library/Application Support/Claude/claude_desktop_config.json` - Linux: `~/.config/Claude/claude_desktop_config.json` Add the following configuration to the `mcpServers` section of your `claude_desktop_config.json`: ```json "anytype": { "command": "uv", "args": [ "run", "--with", "chromadb", "--with", "fastmcp", "--with", "httpx", "--with", "nltk", "--with", "ollama", "--with", "platformdirs", "--with", "sentence-transformers", "fastmcp", "run", "[PATH_TO_ANYTYPE_MCP]/server.py" ] } ``` Replace `[PATH_TO_ANYTYPE_MCP]` with the absolute path to your anytype-mcp directory. For example: - Windows: `C:\\Users\\username\\Documents\\anytype-mcp\\server.py` - macOS/Linux: `/home/username/anytype-mcp/server.py` Make sure to use double backslashes (`\\`) for Windows paths in the JSON file. ## Authentication The server handles authentication with Anytype via a challenge-based flow: 1. First run requires obtaining a challenge ID 2. You'll need to provide a secret code from Anytype 3. The server stores the authentication token for future sessions ## Usage The server provides several tools that can be used within Claude: - `ingest_documents`: Ingest or update Anytype documents into the vector store - `query_anytype_documents`: Perform semantic search across your documents - `get_anytype_object`: Retrieve a specific Anytype object by ID - `get_ingestion_stats`: View statistics about ingested documents - `clear_ingestion`: Clear the vector store and start fresh ## Technical Details ### Embedding Model The `mxbai-embed-large` model is used for generating embeddings in this project. It's fetched from Ollama and configured in the `EmbeddingUtils` class. If you prefer to use a different embedding model, you can modify the `OLLAMA_MODEL` variable in `utils/embedding_utils.py`. ### Data Storage The application uses platformdirs for cross-platform data storage: - ChromaDB data: Stored in a platform-specific user data directory - NLTK data: Downloaded and stored locally - Authentication tokens: Securely stored in a configuration file ### NLTK and Tokenization This project uses the NLTK library for sentence tokenization, specifically the `punkt_tab` tokenizer. The tokenizer is automatically downloaded to the application's data directory during initialization. ## License ## Contributing