Fire in da houseTop Tip:Paying $100+ per month for Perplexity, MidJourney, Runway, ChatGPT and other tools is crazy - get all your AI tools in one site starting at $15 per month with Galaxy AI Fire in da houseCheck it out free

meilisearch-ts-mcp

MCP.Pizza Chef: devlimelabs

meilisearch-ts-mcp is an MCP server implementation that integrates Meilisearch with AI assistants, providing standardized access to index and document management, search capabilities, settings configuration, task monitoring, and system operations. It supports advanced features like vector search and asynchronous task handling, enabling real-time, structured interaction with Meilisearch data stores through the Model Context Protocol.

Use This MCP server To

Create, update, and delete Meilisearch indexes via AI commands Add, update, and remove documents in Meilisearch indexes Perform complex searches with filters and parameters Configure and update Meilisearch index settings programmatically Monitor and manage asynchronous Meilisearch tasks Check system health, version, and statistics of Meilisearch Enable experimental vector search for semantic queries

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

meilisearch-ts-mcp FAQ

How do I install the meilisearch-ts-mcp server?
You can install it easily via Smithery using the command `npx -y @smithery/cli install @devlimelabs/meilisearch-ts-mcp` or follow manual installation instructions on the GitHub repository.
Can meilisearch-ts-mcp handle asynchronous tasks?
Yes, it supports task management to monitor and manage asynchronous operations within Meilisearch.
Does this MCP server support vector search?
Yes, it includes experimental vector search capabilities for semantic and similarity-based queries.
How does meilisearch-ts-mcp improve AI assistant interactions with Meilisearch?
It standardizes and structures access to Meilisearch features, enabling AI models to perform multi-step reasoning and real-time data operations.
What system operations can be performed through this MCP server?
You can perform health checks, retrieve version information, and access system statistics.
Is it possible to configure index settings through this MCP server?
Yes, the server allows full management of index settings programmatically.
What are the benefits of using meilisearch-ts-mcp with multiple LLM providers?
It is provider-agnostic, allowing seamless integration with OpenAI, Claude, Gemini, and others for flexible AI workflows.