Grafana MCP Server
Available Tools
The following tools are available via the MCP server:
- test_connection: Verify connectivity to your Grafana instance and configuration.
- grafana_promql_query: Execute PromQL queries against Grafana's Prometheus datasource. Fetches metrics data using PromQL expressions, optimizes time series responses to reduce token size.
- grafana_loki_query: Query Grafana Loki for log data. Fetches logs for a specified duration (e.g., '5m', '1h', '2d'), converts relative time to absolute timestamps.
- grafana_get_dashboard_config: Retrieves dashboard configuration details from the database. Queries the connectors_connectormetadatamodelstore table for dashboard metadata.
- grafana_query_dashboard_panels: Execute queries for specific dashboard panels. Can query up to 4 panels at once, supports template variables, optimizes metrics data.
- grafana_fetch_label_values: Fetch label values for dashboard variables from Prometheus datasource. Retrieves available values for specific labels (e.g., 'instance', 'job'). Supports optional metric filtering.
- grafana_fetch_dashboard_variables: Fetch all variables and their values from a Grafana dashboard. Retrieves dashboard template variables and their current values.
- grafana_fetch_all_dashboards: Fetch all dashboards from Grafana with basic information like title, UID, folder, tags, etc.
- grafana_fetch_datasources: Fetch all datasources from Grafana with their configuration details.
- grafana_fetch_folders: Fetch all folders from Grafana with their metadata and permissions.
🚀 Usage & Requirements
1. Get Your Grafana API Endpoint & Service Account Token
- Ensure you have a running Grafana instance (self-hosted or cloud).
- Generate a Service Account Token from your Grafana UI:
- Create Service Account: In your Grafana dashboard, navigate to Admin >> Users & Access >> Service Accounts >> Create a Service Account with Viewer permissions
- Generate Service Account Key: Within Service Account, create a new Service Account token.
- Copy the service account token (starts with
glsa_)
2. Installation & Running Options
2A. Install & Run with uv (Recommended for Local Development)
2A.1. Install dependencies with uv
uv venv .venv
source .venv/bin/activate
uv sync
2A.2. Run the server with uv
uv run -m src.grafana_mcp_server.mcp_server
- You can also use
uvto run any other entrypoint scripts as needed. - Make sure your
config.yamlis in the same directory asmcp_server.pyor set the required environment variables (see Configuration section).
2B. Run with Docker Compose (Recommended for Production/Containerized Environments)
- Edit
grafana-mcp-server/src/grafana_mcp_server/config.yamlwith your Grafana details (host, API key). - 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).
3. Configuration
The server loads configuration in the following order of precedence:
- Environment Variables (recommended for Docker/CI):
GRAFANA_HOST: Grafana instance URL (e.g.https://your-grafana-instance.com)GRAFANA_API_KEY: Grafana Service Account Token (required)GRAFANA_SSL_VERIFY:trueorfalse(default:true)MCP_SERVER_PORT: Port to run the server on (default:8000)MCP_SERVER_DEBUG:trueorfalse(default:true)
- YAML file fallback (
config.yaml):grafana: host: "https://your-grafana-instance.com" api_key: "your-grafana-api-key-here" 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 Docker (with environment variables)
{
"mcpServers": {
"grafana": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"-e",
"GRAFANA_HOST",
"-e",
"GRAFANA_API_KEY",
"-e",
"GRAFANA_SSL_VERIFY",
"drdroidlab/grafana-mcp-server",
"-t",
"stdio"
],
"env": {
"GRAFANA_HOST": "https://your-grafana-instance.com",
"GRAFANA_API_KEY": "your-grafana-api-key-here",
"GRAFANA_SSL_VERIFY": "true"
}
}
}
}
- The
-t stdioargument is supported for compatibility with Docker MCP clients (forces stdio handshake mode). - Adjust the volume path or environment variables as needed for your deployment.
4B. 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.
{
"mcpServers": {
"grafana": {
"url": "http://your-server-host:8000/mcp"
}
}
}
- Replace
your-server-hostwith the actual host where your MCP server is running. - For local setup, use
localhostas the server host (i.e.,http://localhost:8000/mcp). - Use
httpfor local or unsecured deployments, andhttpsfor production or secured deployments. - Make sure the server is accessible from your client machine (check firewall, security group, etc.).
Health Check
curl http://localhost:8000/health
The server runs on port 8000 by default.
5. Project Structure
grafana-mcp-server/
│ └── src/
│ └── grafana_mcp_server/
│ ├── __init__.py
│ ├── config.yaml # Configuration file
│ ├── mcp_server.py # Main MCP server implementation
│ ├── stdio_server.py # STDIO server for MCP
│ └── processor/
│ ├── __init__.py
│ ├── grafana_processor.py # Grafana API processor
│ └── processor.py # Base processor interface
├── tests/
├── Dockerfile
├── docker-compose.yml
├── pyproject.toml
└── README.md
6. Troubleshooting
Common Issues
-
Connection Failed:
- Verify your Grafana instance is running and accessible
- Check your API key has proper permissions
- Ensure SSL verification settings match your setup
-
Authentication Errors:
- Verify your API key is correct and not expired
- Check if your Grafana instance requires additional authentication
-
Query Failures:
- Ensure datasource UIDs are correct
- Verify PromQL/Loki query syntax
- Check if the datasource is accessible with your API key
Debug Mode
Enable debug mode to get more detailed logs:
export MCP_SERVER_DEBUG=true
7. Contributing
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add some amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
8. License
This project is licensed under the MIT License - see the LICENSE file for details.
9. Support
- Need help anywhere? Join our discord channel and message on #mcp channel.
- Want a 1-click MCP Server? Join the same community and let us know.
- For issues and questions, please open an issue on GitHub or contact the maintainers.