Grafana

MCP server forGrafana— manage dashboards, datasources, alert rules, folders, and annotations over stdio.

{ "mcpServers": { "grafana": { "type": "stdio", "command": "bunx", "args": ["@daanrongen/grafana-mcp"], "env": { "GRAFANA_URL": "http://localhost:3000", "GRAFANA_API_KEY": "your-service-account-token" } } } }

claude mcp add grafana \ -e GRAFANA_URL=http://localhost:3000 \ -e GRAFANA_API_KEY=your-service-account-token \ -- bunx @daanrongen/grafana-mcp

bun install bun run dev # run with --watch bun test # run test suite bun run typecheck # type-check with tsc bun run lint # biome lint bun run format # biome format bun run build # bundle to dist/main.js

Use the MCP Inspector to browse and call tools interactively against a real Grafana instance:

GRAFANA_URL=http://localhost:3000 \ GRAFANA_API_KEY=your-service-account-token \ bun run inspect

This opens the MCP Inspector UI in the browser, pointed at the locally built server.

src/ ├── config.ts # Effect Config — GRAFANA_URL, GRAFANA_API_KEY ├── main.ts # Entry point — ManagedRuntime + StdioServerTransport ├── domain/ │ ├── GrafanaClient.ts # Context.Tag service interface (port) │ ├── errors.ts # GrafanaError, NotFoundError │ ├── models.ts # Schema.Class models (Dashboard, Datasource, AlertRule, …) │ ├── dashboards.test.ts # Domain tests using GrafanaClientTest │ ├── datasources.test.ts # Domain tests using GrafanaClientTest │ └── health.test.ts # Domain tests using GrafanaClientTest ├── infra/ │ ├── GrafanaClientLive.ts # Layer using fetch against the Grafana HTTP API │ └── GrafanaClientTest.ts # In-memory Ref-based test adapter └── mcp/ ├── server.ts # McpServer wired to ManagedRuntime ├── utils.ts # formatSuccess, formatError └── tools/ # dashboards.ts, datasources.ts, alerts.ts, folders.ts, annotations.ts, health.ts

Access Grafana resources like dashboards, datasources, Prometheus, Loki, and alerts.

Access and manage Grafana resources, including dashboards, datasources, Prometheus, Loki, and alerting.

Interact with Honeycomb observability data using the Model Context Protocol.

Access Prometheus metrics and queries through standardized MCP interfaces.

Interact with your Prometheus monitoring infrastructure using natural language.

An MCP server for integrating with Prometheus to query metrics.

A server for querying Loki logs from Grafana.

An MCP server for log analysis using the LogAI framework, with optional Grafana and GitHub integrations.

A Go-based server to query Grafana Loki logs using the Model Context Protocol (MCP).

Expose Prometheus monitoring tools to an LLM for querying and analysis.