meilisearch ts mcp
Enables AI assistants to interact with Meilisearch via the Model Context Protocol, allowing comprehensive index, document, and search management through a standardized interface.
Enables AI assistants to interact with Meilisearch via the Model Context Protocol, allowing comprehensive index, document, and search management through a standardized interface.
A Model Context Protocol (MCP) server implementation for Meilisearch, enabling AI assistants to interact with Meilisearch through a standardized interface.
To install Meilisearch MCP Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @devlimelabs/meilisearch-ts-mcp --client claude
Clone the repository:
git clone https://github.com/devlimelabs/meilisearch-ts-mcp.git
cd meilisearch-ts-mcp
Install dependencies:
npm install
Create a .env
file based on the example:
cp .env.example .env
Edit the .env
file to configure your Meilisearch connection.
The Meilisearch MCP Server can be run in a Docker container for easier deployment and isolation.
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
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
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 does not 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
npm run build
npm start
npm run dev
The Meilisearch MCP Server can be integrated with Claude for Desktop, allowing you to interact with your Meilisearch instance directly through Claude.
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
If you prefer to manually configure Claude for Desktop:
~/Library/Application Support/Claude/claude_desktop_config.json
%APPDATA%Claudeclaude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json
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"
}
}
}
}
Restart Claude for Desktop to apply the changes.
In Claude, type: "I want to use the Meilisearch MCP server" to activate the integration.
The Meilisearch MCP Server can also be integrated with Cursor, an AI-powered code editor.
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
Start the MCP server:
npm start
In Cursor, open the Command Palette (Cmd/Ctrl+Shift+P) and search for "MCP: Connect to MCP Server".
Select "Connect to a local MCP server" and enter the following details:
Environment Variables:
MEILISEARCH_HOST=http://localhost:7700
MEILISEARCH_API_KEY=your-api-key
Click "Connect" to establish the connection.
You can now interact with your Meilisearch instance through Cursor by typing commands like "Search my Meilisearch index for documents about..."
The Meilisearch MCP Server provides the following tools:
create-index
: Create a new indexget-index
: Get information about an indexlist-indexes
: List all indexesupdate-index
: Update an indexdelete-index
: Delete an indexadd-documents
: Add documents to an indexget-document
: Get a document by IDget-documents
: Get multiple documentsupdate-documents
: Update documentsdelete-document
: Delete a document by IDdelete-documents
: Delete multiple documentsdelete-all-documents
: Delete all documents in an indexsearch
: Search for documentsmulti-search
: Perform multiple searches in a single requestget-settings
: Get index settingsupdate-settings
: Update index settingsreset-settings
: Reset index settings to defaultlist-tasks
: List tasks with optional filteringget-task
: Get information about a specific taskcancel-tasks
: Cancel tasks based on provided filterswait-for-task
: Wait for a specific task to completehealth
: Check the health status of the Meilisearch serverversion
: Get version informationinfo
: Get system informationstats
: Get statistics about indexesenable-vector-search
: Enable vector searchget-experimental-features
: Get experimental features statusupdate-embedders
: Configure embeddersget-embedders
: Get embedders configurationreset-embedders
: Reset embedders configurationvector-search
: Perform vector searchMIT