Meilisearch MCP Server

Meilisearch MCP Server

Enables AI assistants to interact with Meilisearch through a standardized interface, supporting index and document management, search capabilities, settings configuration, task monitoring, and experimental vector search.

Category
Visit Server

README

Meilisearch MCP Server

smithery badge

A Model Context Protocol (MCP) server implementation for Meilisearch, enabling AI assistants to interact with Meilisearch through a standardized interface.

Features

  • Index Management: Create, update, and delete indexes
  • Document Management: Add, update, and delete documents
  • Search Capabilities: Perform searches with various parameters and filters
  • Settings Management: Configure index settings
  • Task Management: Monitor and manage asynchronous tasks
  • System Operations: Health checks, version information, and statistics
  • Vector Search: Experimental vector search capabilities

Installation

Installing via Smithery

To install Meilisearch MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @devlimelabs/meilisearch-ts-mcp --client claude

Manual Installation

  1. Clone the repository:

    git clone https://github.com/devlimelabs/meilisearch-ts-mcp.git
    cd meilisearch-ts-mcp
    
  2. Install dependencies:

    npm install
    
  3. Create a .env file based on the example:

    cp .env.example .env
    
  4. Edit the .env file to configure your Meilisearch connection.

Docker Setup

The Meilisearch MCP Server can be run in a Docker container for easier deployment and isolation.

Using Docker Compose

The easiest way to get started with Docker is to use Docker Compose:

# Start the Meilisearch MCP Server
docker-compose up -d

# View logs
docker-compose logs -f

# Stop the server
docker-compose down

Building and Running the Docker Image Manually

You can also build and run the Docker image manually:

# Build the Docker image
docker build -t meilisearch-ts-mcp .

# Run the container
docker run -p 3000:3000 --env-file .env meilisearch-ts-mcp

Development Setup

For developers who want to contribute to the Meilisearch MCP Server, we provide a convenient setup script:

# Clone the repository
git clone https://github.com/devlimelabs-ts-mcp/meilisearch-ts-mcp.git
cd meilisearch-ts-mcp

# Run the development setup script
./scripts/setup-dev.sh

The setup script will:

  1. Create a .env file from .env.example if it doesn't exist
  2. Install dependencies
  3. Build the project
  4. Run tests to ensure everything is working correctly

After running the setup script, you can start the server in development mode:

npm run dev

Usage

Building the Project

npm run build

Running the Server

npm start

Development Mode

npm run dev

Claude Desktop Integration

The Meilisearch MCP Server can be integrated with Claude for Desktop, allowing you to interact with your Meilisearch instance directly through Claude.

Automated Setup

We provide a setup script that automatically configures Claude for Desktop to work with the Meilisearch MCP Server:

# First build the project
npm run build

# Then run the setup script
node scripts/claude-desktop-setup.js

The script will:

  1. Detect your operating system and locate the Claude for Desktop configuration file
  2. Read your Meilisearch configuration from the .env file
  3. Generate the necessary configuration for Claude for Desktop
  4. Provide instructions for updating your Claude for Desktop configuration

Manual Setup

If you prefer to manually configure Claude for Desktop:

  1. Locate your Claude for Desktop configuration file:

    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: %APPDATA%\Claude\claude_desktop_config.json
    • Linux: ~/.config/Claude/claude_desktop_config.json
  2. Add the following configuration (adjust paths as needed):

{
  "mcpServers": {
    "meilisearch": {
      "command": "node",
      "args": ["/path/to/meilisearch-ts-mcp/dist/index.js"],
      "env": {
        "MEILISEARCH_HOST": "http://localhost:7700",
        "MEILISEARCH_API_KEY": "your-api-key"
      }
    }
  }
}
  1. Restart Claude for Desktop to apply the changes.

  2. In Claude, type: "I want to use the Meilisearch MCP server" to activate the integration.

Cursor Integration

The Meilisearch MCP Server can also be integrated with Cursor, an AI-powered code editor.

Setting Up MCP in Cursor

  1. Install and set up the Meilisearch MCP Server:

    git clone https://github.com/devlimelabs/meilisearch-ts-mcp.git
    cd meilisearch-ts-mcp
    npm install
    npm run build
    
  2. Start the MCP server:

    npm start
    
  3. In Cursor, open the Command Palette (Cmd/Ctrl+Shift+P) and search for "MCP: Connect to MCP Server".

  4. Select "Connect to a local MCP server" and enter the following details:

    • Name: Meilisearch
    • Command: node
    • Arguments: /absolute/path/to/meilisearch-ts-mcp/dist/index.js
    • Environment Variables:
      MEILISEARCH_HOST=http://localhost:7700
      MEILISEARCH_API_KEY=your-api-key
      
  5. Click "Connect" to establish the connection.

  6. You can now interact with your Meilisearch instance through Cursor by typing commands like "Search my Meilisearch index for documents about..."

Available Tools

The Meilisearch MCP Server provides the following tools:

Index Tools

  • create-index: Create a new index
  • get-index: Get information about an index
  • list-indexes: List all indexes
  • update-index: Update an index
  • delete-index: Delete an index

Document Tools

  • add-documents: Add documents to an index
  • get-document: Get a document by ID
  • get-documents: Get multiple documents
  • update-documents: Update documents
  • delete-document: Delete a document by ID
  • delete-documents: Delete multiple documents
  • delete-all-documents: Delete all documents in an index

Search Tools

  • search: Search for documents
  • multi-search: Perform multiple searches in a single request

Settings Tools

  • get-settings: Get index settings
  • update-settings: Update index settings
  • reset-settings: Reset index settings to default
  • Various specific settings tools (synonyms, stop words, ranking rules, etc.)

Task Tools

  • list-tasks: List tasks with optional filtering
  • get-task: Get information about a specific task
  • cancel-tasks: Cancel tasks based on provided filters
  • wait-for-task: Wait for a specific task to complete

System Tools

  • health: Check the health status of the Meilisearch server
  • version: Get version information
  • info: Get system information
  • stats: Get statistics about indexes

Vector Tools (Experimental)

  • enable-vector-search: Enable vector search
  • get-experimental-features: Get experimental features status
  • update-embedders: Configure embedders
  • get-embedders: Get embedders configuration
  • reset-embedders: Reset embedders configuration
  • vector-search: Perform vector search

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured