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# Chroma MCP Server A Model Context Protocol (MCP) server implementation that provides vector database capabilities through Chroma. This server enables semantic document search, metadata filtering, and document management with persistent storage. ## Requirements - Python 3.8+ - Chroma 0.4.0+ - MCP SDK 0.1.0+ ## Components ### Resources The server provides document storage and retrieval through Chroma's vector database: - Stores documents with content and metadata - Persists data in `src/chroma/data` directory - Supports semantic similarity search ### Tools The server implements CRUD operations and search functionality: #### Document Management - `create_document`: Create a new document - Required: `document_id`, `content` - Optional: `metadata` (key-value pairs) - Returns: Success confirmation - Error: Already exists, Invalid input - `read_document`: Retrieve a document by ID - Required: `document_id` - Returns: Document content and metadata - Error: Not found - `update_document`: Update an existing document - Required: `document_id`, `content` - Optional: `metadata` - Returns: Success confirmation - Error: Not found, Invalid input - `delete_document`: Remove a document - Required: `document_id` - Returns: Success confirmation - Error: Not found - `list_documents`: List all documents - Optional: `limit`, `offset` - Returns: List of documents with content and metadata #### Search Operations - `search_similar`: Find semantically similar documents - Required: `query` - Optional: `num_results`, `metadata_filter`, `content_filter` - Returns: Ranked list of similar documents with distance scores - Error: Invalid filter ## Features - **Semantic Search**: Find documents based on meaning using Chroma's embeddings - **Metadata Filtering**: Filter search results by metadata fields - **Content Filtering**: Additional filtering based on document content - **Persistent Storage**: Data persists in local directory between serv…
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