Signoz MCP Server

Signoz MCP Server

Watch Working Demo on Cursor 📽️ https://youtube.com/shorts/jxjmGyXXz7A

Available Tools

The following tools are available via the MCP server:

• test_connection: Verify connectivity to your Signoz instance and configuration.
• fetch_dashboards: List all available dashboards from Signoz.
• fetch_dashboard_details: Retrieve detailed information about a specific dashboard by its ID. This information contains the metadata of the dashboard, not the live panel data.
• fetch_dashboard_data: Fetch all panel data for a given dashboard by name and time range.
• fetch_apm_metrics: Retrieve standard APM metrics (request rate, error rate, latency, apdex, etc.) for a given service and time range.
• fetch_services: Fetch all instrumented services from Signoz with optional time range filtering.
• execute_clickhouse_query: Execute custom Clickhouse SQL queries via the Signoz API with time range support.
• execute_builder_query: Execute Signoz builder queries for custom metrics and aggregations with time range support.
• fetch_traces_or_logs: Fetch traces or logs from SigNoz using ClickHouse SQL. Specify data_type ('traces' or 'logs'), time range, service name, and limit. Returns tabular results for traces or logs.

🚀 Usage & Requirements

1. Get Your Signoz API Endpoint & (Optional) API Key

1. Ensure you have a running Signoz instance (self-hosted or cloud).
2. (Optional) If your Signoz instance requires an API key for the health endpoint, generate or obtain it from your Signoz UI.

2. Installation & Running Options

2A. Install & Run with uv (Recommended for Local Development)

2A.1. Install dependencies with uv

2A.2. Run the server with uv

• You can also use uv to run any other entrypoint scripts as needed.
• Make sure your config.yaml is in the same directory as mcp_server.py or set the required environment variables (see Configuration section).

2B. Run with Docker Compose (Recommended for Production/Containerized Environments)

1. Edit src/signoz_mcp_server/config.yaml with your Signoz details (host, API key if needed).
2. Start the server:
   docker-compose up -d
   • The server will run in HTTP (SSE) mode on port 8000 by default.
   • You can override configuration with environment variables (see below).

2C. Run with Docker Image (Manual)

1. Build the image:
   docker build -t signoz-mcp-server .
2. Run the container (YAML config fallback):
   docker run -d \ -p 8000:8000 \ -v $(pwd)/src/signoz_mcp_server/config.yaml:/app/config.yaml:ro \ --name signoz-mcp-server \ signoz-mcp-server
3. Or run with environment variables (recommended for CI/Docker MCP clients):
   docker run -d \ -p 8000:8000 \ -e SIGNOZ_HOST="https://your-signoz-instance.com" \ -e SIGNOZ_API_KEY="your-signoz-api-key-here" \ -e SIGNOZ_SSL_VERIFY="true" \ -e MCP_SERVER_PORT=8000 \ -e MCP_SERVER_DEBUG=true \ --name signoz-mcp-server \ signoz-mcp-server

3. Configuration

The server loads configuration in the following order of precedence:

1. Environment Variables (recommended for Docker/CI):
   • SIGNOZ_HOST: Signoz instance URL (e.g. https://your-signoz-instance.com)
   • SIGNOZ_API_KEY: Signoz API key (optional)
   • SIGNOZ_SSL_VERIFY: true or false (default: true)
   • MCP_SERVER_PORT: Port to run the server on (default: 8000)
   • MCP_SERVER_DEBUG: true or false (default: true)
2. YAML file fallback (config.yaml):
   signoz: host: "https://your-signoz-instance.com" api_key: "your-signoz-api-key-here" # Optional ssl_verify: "true" server: port: 8000 debug: true

4. Integration with AI Assistants (e.g., Claude Desktop, Cursor)

You can integrate this MCP server with any tool that supports the MCP protocol. Here are the main options:

4A. Using Local Setup (with uv)

Before running the server locally, install dependencies and run with uv:

Then add to your client configuration (e.g., claude-desktop.json):

• Ensure your config.yaml is in the same directory as mcp_server.py or update the path accordingly.

4B. Using Docker Compose or Docker (with environment variables, mcp-grafana style)

• The -t stdio argument is supported for compatibility with Docker MCP clients (forces stdio handshake mode).
• Adjust the volume path or environment variables as needed for your deployment.

4C. Connecting to an Already Running MCP Server (HTTP/SSE)

If you have an MCP server already running (e.g., on a remote host, cloud VM, or Kubernetes), you can connect your AI assistant or tool directly to its HTTP endpoint.

Example: Claude Desktop or Similar Tool

• Replace your-server-host with the actual host where your MCP server is running.
• For local setup, use localhost as the server host (i.e., http://localhost:8000/mcp).
• Use http for local or unsecured deployments, and https for production or secured deployments.
• Make sure the server is accessible from your client machine (check firewall, security group, etc.).

Example: MCP Config YAML

• Replace your-server-host with the actual host where your MCP server is running.
• For local setup, use localhost as the server host (i.e., http://localhost:8000/mcp).
• Use http or https in the URL schema depending on how you've deployed the MCP server.
• No need to specify command or args—just point to the HTTP endpoint.
• This works for any tool or assistant that supports MCP over HTTP.
• The server must be running in HTTP (SSE) mode (the default for this implementation).

Health Check

The server runs on port 8000 by default.

5. Miscellaneous:

1. Need help anywhere? Join our slack community and message on #mcp channel.
2. Want a 1-click MCP Server? Join the same comunity and let us know.