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mcp-typesense-server

MCP.Pizza Chef: suhail-ak-s

The mcp-typesense-server is an MCP server implementation that integrates Typesense search capabilities with AI models. It allows large language models to discover, query, and analyze data stored in Typesense collections through standardized MCP interfaces. This server exposes collections with metadata and schema access, enabling real-time, structured search and retrieval workflows within AI-enhanced applications.

Use This MCP server To

Enable LLMs to perform real-time search on Typesense collections Expose Typesense collection metadata and schemas to AI models Allow AI models to query and analyze structured data in Typesense Integrate Typesense search into AI-powered workflows and agents Support multi-collection search and data discovery via MCP Facilitate building AI copilots that leverage Typesense search

README

Typesense MCP Server


npm version License: MIT Node.js Version

A Model Context Protocol (MCP) server implementation that provides AI models with access to Typesense search capabilities. This server enables LLMs to discover, search, and analyze data stored in Typesense collections.

Demo

Typesense MCP Server Demo | Claude Desktop

Features

Resources

  • List and access collections via typesense:// URIs
  • Each collection has a name, description, and document count
  • JSON mime type for schema access

Tools

  • typesense_query

    • Search for documents in Typesense collections with powerful filtering
    • Input: Query text, collection name, search fields, filters, sort options, limit
    • Returns matching documents with relevance scores
  • typesense_get_document

    • Retrieve specific documents by ID from collections
    • Input: Collection name, document ID
    • Returns complete document data
  • typesense_collection_stats

    • Get statistics about a Typesense collection
    • Input: Collection name
    • Returns collection metadata, document count, and schema information

Prompts

  • analyze_collection

    • Analyze collection structure and contents
    • Input: Collection name
    • Output: Insights about schema, data types, and statistics
  • search_suggestions

    • Get suggestions for effective search queries for a collection
    • Input: Collection name
    • Output: Recommended search strategies based on collection schema

Installation

Via npm

# Global installation
npm install -g typesense-mcp-server

# Local installation
npm install typesense-mcp-server

Via mcp-get

npx @michaellatman/mcp-get@latest install typesense-mcp-server

Development

Install dependencies:

npm install

Build the server:

npm run build

For development with auto-rebuild:

npm run watch

Installation for Development

Using Claude Desktop

To use with Claude Desktop, add the server config:

On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json

On Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "typesense": {
      "command": "node",
      "args": [
        "~/typesense-mcp-server/dist/index.js",
        "--host", "your-typesense-host",
        "--port", "8108",
        "--protocol", "http",
        "--api-key", "your-api-key"
      ]
    },
  }
}

Debugging

Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:

npm run inspector

The Inspector will provide a URL to access debugging tools in your browser.

Components

Resources

The server provides information about Typesense collections:

  • Collection Schemas (typesense://collections/<collection>)
    • JSON schema information for each collection
    • Includes field names and data types
    • Sample documents for understanding data structure

Resource Templates

The server provides templates for:

  • typesense_search - Template for constructing Typesense search queries
  • typesense_collection - Template for viewing Typesense collection details

Usage with Claude Desktop

To use this server with the Claude Desktop app, add the following configuration to the "mcpServers" section of your claude_desktop_config.json:

{
  "mcpServers": {
    "typesense": {
      "command": "npx",
      "args": [
        "-y",
        "typesense-mcp-server",
        "--host", "your-typesense-host",
        "--port", "8108",
        "--protocol", "http",
        "--api-key", "your-api-key"
      ]
    }
  }
}

Logging

The server logs information to a file located at:

/tmp/typesense-mcp.log

This log contains detailed information about server operations, requests, and any errors that occur.

License

This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.

mcp-typesense-server FAQ

How does mcp-typesense-server connect AI models to Typesense?
It exposes Typesense collections and search APIs via MCP, allowing LLMs to query and analyze data.
What data formats does mcp-typesense-server support?
It supports JSON mime type for schema access and document retrieval from Typesense collections.
Can mcp-typesense-server handle multiple collections?
Yes, it lists and provides access to multiple Typesense collections with metadata.
Is mcp-typesense-server compatible with different LLM providers?
Yes, it works with OpenAI, Anthropic Claude, and Google Gemini models via the MCP protocol.
What are the prerequisites for running mcp-typesense-server?
You need a running Typesense instance and Node.js environment to deploy the server.
How does mcp-typesense-server improve AI workflows?
It enables AI models to perform structured search and data analysis directly on Typesense indexes.
Is the mcp-typesense-server open source?
Yes, it is MIT licensed and available on npm for easy integration.
How do I access collection schemas via mcp-typesense-server?
Schemas are accessible in JSON format through the MCP server endpoints.