Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Chroma MCP Serversearch for documents about neural networks with metadata field 'computer vision'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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+
Related MCP server: doc-lib-mcp
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/datadirectorySupports semantic similarity search
Tools
The server implements CRUD operations and search functionality:
Document Management
create_document: Create a new documentRequired:
document_id,contentOptional:
metadata(key-value pairs)Returns: Success confirmation
Error: Already exists, Invalid input
read_document: Retrieve a document by IDRequired:
document_idReturns: Document content and metadata
Error: Not found
update_document: Update an existing documentRequired:
document_id,contentOptional:
metadataReturns: Success confirmation
Error: Not found, Invalid input
delete_document: Remove a documentRequired:
document_idReturns: Success confirmation
Error: Not found
list_documents: List all documentsOptional:
limit,offsetReturns: List of documents with content and metadata
Search Operations
search_similar: Find semantically similar documentsRequired:
queryOptional:
num_results,metadata_filter,content_filterReturns: 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 server restarts
Error Handling: Comprehensive error handling with clear messages
Retry Logic: Automatic retries for transient failures
Installation
Install dependencies:
Configuration
Claude Desktop
Add the server configuration to your Claude Desktop config:
Windows: C:\Users\<username>\AppData\Roaming\Claude\claude_desktop_config.json
MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Data Storage
The server stores data in:
Windows:
src/chroma/dataMacOS/Linux:
src/chroma/data
Usage
Start the server:
Use MCP tools to interact with the server:
Error Handling
The server provides clear error messages for common scenarios:
Document already exists [id=X]Document not found [id=X]Invalid input: Missing document_id or contentInvalid filterOperation failed: [details]
Development
Testing
Run the MCP Inspector for interactive testing:
Use the inspector's web interface to:
Test CRUD operations
Verify search functionality
Check error handling
Monitor server logs
Building
Update dependencies:
Build package:
Contributing
Contributions are welcome! Please read our Contributing Guidelines for details on:
Code style
Testing requirements
Pull request process
License
This project is licensed under the MIT License - see the LICENSE file for details.