Elasticsearch MCP Server

# Elasticsearch MCP Server Connect to your Elasticsearch data directly from any MCP Client (like Claude Desktop) using the Model Context Protocol (MCP). This server connects agents to your Elasticsearch data using the Model Context Protocol. It allows you to interact with your Elasticsearch indices through natural language conversations. ## Features * **List Indices**: View all available Elasticsearch indices * **Get Mappings**: Inspect field mappings for specific indices * **Search**: Execute Elasticsearch queries using full Query DSL capabilities with automatic highlighting ## Prerequisites * An Elasticsearch instance * Elasticsearch API key with appropriate permissions * MCP Client (e.g. Claude Desktop) ## Demo https://github.com/user-attachments/assets/5dd292e1-a728-4ca7-8f01-1380d1bebe0c ## Installation & Setup ### Using the Published NPM Package > [!TIP] > The easiest way to use Elasticsearch MCP Server is through the published npm package. 1. **Configure MCP Client** - Open your MCP Client. See the [list of MCP Clients](https://modelcontextprotocol.io/clients), here we are configuring Claude Desktop. - Go to **Settings > Developer > MCP Servers** - Click `Edit Config` and add a new MCP Server with the following configuration: ```json { "mcpServers": { "elasticsearch-mcp-server": { "command": "npx", "args": [ "-y", "@elastic/mcp-server-elasticsearch" ], "env": { "ES_URL": "your-elasticsearch-url", "ES_API_KEY": "your-api-key" } } } } ``` 2. **Start a Conversation** - Open a new conversation in your MCP Client - The MCP server should connect automatically - You can now ask questions about your Elasticsearch data ### Developing Locally > [!NOTE] > If you want to modify or extend the MCP Server, follow these local development steps. 1. **Use the correct Node.js version** ```bash nvm use ``` 2. **Install Dependencies** ```bash npm install ``` 3. **Build the Project** ```bash npm run build ``` 4. **Run locally in Claude Desktop App** - Open **Claude Desktop App** - Go to **Settings > Developer > MCP Servers** - Click `Edit Config` and add a new MCP Server with the following configuration: ```json { "mcpServers": { "elasticsearch-mcp-server-local": { "command": "node", "args": [ "/path/to/your/project/dist/index.js" ], "env": { "ES_URL": "your-elasticsearch-url", "ES_API_KEY": "your-api-key" } } } } ``` 5. **Debugging with MCP Inspector** ```bash ES_URL=your-elasticsearch-url ES_API_KEY=your-api-key npm run inspector ``` This will start the MCP Inspector, allowing you to debug and analyze requests. Ensure that the necessary environment variables (`ES_URL` and `ES_API_KEY`) are exposed when starting the inspector. You should see output similar to: ```bash Starting MCP inspector... Proxy server listening on port 3000 🔍 MCP Inspector is up and running at http://localhost:5173 🚀 ``` ## Example Questions > [!TIP] > Here are some natural language queries you can try with your MCP Client. * "What indices do I have in my Elasticsearch cluster?" * "Show me the field mappings for the 'products' index." * "Find all orders over $500 from last month." * "Which products received the most 5-star reviews?" ## How It Works 1. The MCP Client analyzes your request and determines which Elasticsearch operations are needed. 2. The MCP server carries out these operations (listing indices, fetching mappings, performing searches). 3. The MCP Client processes the results and presents them in a user-friendly format. ## Security Best Practices > [!WARNING] > Avoid using cluster-admin privileges. Create dedicated API keys with limited scope and apply fine-grained access control at the index level to prevent unauthorized data access. You can create a dedicated Elasticsearch API key with minimal permissions to control access to your data: ``` POST /_security/api_key { "name": "es-mcp-server-access", "role_descriptors": { "mcp_server_role": { "cluster": [ "monitor" ], "indices": [ { "names": [ "index-1", "index-2", "index-pattern-*" ], "privileges": [ "read", "view_index_metadata" ] } ] } } } ``` ## Troubleshooting * Ensure your MCP configuration is correct. * Verify that your Elasticsearch URL is accessible from your machine. * Check that your API key has the necessary permissions. * Look at the terminal output for error messages. If you encounter issues, feel free to open an issue on the GitHub repository.