Weaviate MCP Server

1

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claude mcp add mcp-weaviate -- uvx mcp-weaviate --help
README.md

Seamless integration with Weaviate vector databases for search and management.

Weaviate MCP Server

A Model Context Protocol (MCP) server that provides seamless integration with Weaviate vector databases. This server focuses on powerful search capabilities including semantic, keyword, and hybrid search, with plans to expand functionality in future releases.

Features

The Weaviate MCP Server currently provides 11 essential tools for interacting with your Weaviate instance:

Connection & Configuration

  • get_config - View current Weaviate configuration (with sensitive values masked)
  • check_connection - Test connection to your Weaviate instance

Schema & Collection Management

  • list_collections - List all available collections in your database
  • get_schema - Get detailed schema information for specific collections or all collections
  • get_collection_objects - Retrieve objects from collections with pagination support

Search Capabilities (Primary Focus)

  • search - Simplified search interface using hybrid search by default
  • semantic_search - Vector similarity search using embeddings for semantic matching
  • keyword_search - BM25-based keyword search for exact term matching
  • hybrid_search - Combined semantic and keyword search with configurable weighting

Multi-Tenancy Support

  • is_multi_tenancy_enabled - Check if a collection supports multi-tenancy
  • get_tenant_list - List all tenants for a multi-tenant collection

Quick Start

The MCP server is designed to be used with MCP clients like Claude Desktop. It uses uvx for automatic installation and execution - no manual installation required.

Test the server directly:

uvx mcp-weaviate --help

Requirements

  • Weaviate instance (local or cloud)
  • API keys for embeddings:
    • OpenAI API key (for OpenAI embeddings)
    • Cohere API key (optional, for Cohere embeddings)

Configuration

MCP Settings Configuration

Add the Weaviate MCP server to your MCP settings file (typically claude_desktop_config.json or similar):

Local Weaviate Instance
{
  "mcpServers": {
    "mcp-weaviate": {
      "command": "/path/to/uvx",
      "args": [
        "mcp-weaviate",
        "--connection-type", "local",
        "--host", "localhost",
        "--port", "8080",
        "--grpc-port", "50051",
        "--openai-api-key", "YOUR_OPENAI_API_KEY"
      ]
    }
  }
}
Weaviate Cloud Services
{
  "mcpServers": {
    "mcp-weaviate": {
      "command": "/path/to/uvx",
      "args": [
        "mcp-weaviate",
        "--connection-type", "cloud",
        "--cluster-url", "https://your-cluster.weaviate.network",
        "--api-key", "YOUR_WEAVIATE_API_KEY",
        "--openai-api-key", "YOUR_OPENAI_API_KEY"
      ]
    }
  }
}

Configuration Options

Option Description Default Environment Variable
--transport Transport protocol: "stdio" or "streamable-http" stdio -
--http-host Host for HTTP transport 0.0.0.0 -
--http-port Port for HTTP transport 8000 -
--connection-type Connection type: "local" or "cloud" required -
--host Host for local Weaviate connection required for local -
--port HTTP port for local Weaviate connection required for local -
--grpc-port gRPC port for local Weaviate connection required for local -
--cluster-url Weaviate Cloud Services URL required for cloud WEAVIATE_CLUSTER_URL
--api-key API key for authentication required for cloud WEAVIATE_API_KEY
--openai-api-key OpenAI API key for embeddings - OPENAI_API_KEY
--cohere-api-key Cohere API key for embeddings - COHERE_API_KEY
--timeout-init Initialization timeout (seconds) 30 -
--timeout-query Query timeout (seconds) 60 -
--timeout-insert Insert timeout (seconds) 120 -

Remote Deployment

For deploying the MCP server remotely (e.g., on TrueFoundry, Kubernetes, etc.), use the streamable-http transport:

mcp-weaviate --transport streamable-http --http-port 8000 --connection-type cloud

This exposes the server on HTTP port 8000 with a /health endpoint for health checks.

Tool Reference

Search Tools

`search`

Simplified search interface using hybrid search with balanced defaults (alpha=0.3).

`semantic_search`

Vector similarity search using embeddings. Best for finding conceptually similar content.

`keyword_search`

BM25 keyword search for exact term matching. Best for finding specific terms or phrases.

`hybrid_search`

Combines semantic and keyword search using Reciprocal Rank Fusion (RRF).

  • alpha parameter controls the balance:
    • 1.0 = 100% semantic search
    • 0.0 = 100% keyword search
    • 0.5 = equal weight
    • 0.3 = default (30% semantic, 70% keyword)

Collection Management

`get_collection_objects`

Retrieve objects from a collection with pagination

Tools (7)

searchSimplified search interface using hybrid search by default.
semantic_searchVector similarity search using embeddings for semantic matching.
keyword_searchBM25-based keyword search for exact term matching.
hybrid_searchCombined semantic and keyword search with configurable weighting.
list_collectionsList all available collections in your database.
get_schemaGet detailed schema information for specific collections or all collections.
get_collection_objectsRetrieve objects from collections with pagination support.

Environment Variables

WEAVIATE_CLUSTER_URLWeaviate Cloud Services URL
WEAVIATE_API_KEYAPI key for authentication
OPENAI_API_KEYOpenAI API key for embeddings
COHERE_API_KEYCohere API key for embeddings

Configuration

claude_desktop_config.json
{"mcpServers": {"mcp-weaviate": {"command": "uvx", "args": ["mcp-weaviate", "--connection-type", "local", "--host", "localhost", "--port", "8080", "--grpc-port", "50051", "--openai-api-key", "YOUR_OPENAI_API_KEY"]}}}

Try it

List all the collections currently available in my Weaviate database.
Perform a hybrid search for 'customer support documentation' in the 'knowledge_base' collection.
Get the schema details for the 'products' collection.
Retrieve the first 10 objects from the 'user_feedback' collection.
Check if the 'multi_tenant_data' collection has multi-tenancy enabled.

Frequently Asked Questions

What are the key features of Weaviate MCP Server?

Supports semantic, keyword, and hybrid search capabilities. Provides schema management and collection retrieval tools. Includes multi-tenancy support checks. Compatible with both local and cloud Weaviate instances. Configurable search weighting using alpha parameters.

What can I use Weaviate MCP Server for?

Querying internal knowledge bases using semantic search for better context retrieval. Managing and inspecting database schemas directly from the AI interface. Retrieving specific data objects from collections for analysis or summarization. Testing and validating Weaviate connection configurations. Performing hybrid searches to balance exact keyword matching with conceptual similarity.

How do I install Weaviate MCP Server?

Install Weaviate MCP Server by running: uvx mcp-weaviate --help

What MCP clients work with Weaviate MCP Server?

Weaviate MCP Server works with any MCP-compatible client including Claude Desktop, Claude Code, Cursor, and other editors with MCP support.

Turn this server into reusable context

Keep Weaviate MCP Server docs, env vars, and workflow notes in Conare so your agent carries them across sessions.

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