What tools does Grafana MCP provide?
It provides `get_grafana_info()`, `list_dashboards()`, `get_dashboard(uid)`, `get_organization()`, and `list_datasources()`.
@izaitsevfb
基本情報
MCP server for grafana
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"grafana-mcp-izaitsevfb": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
Grafana MCP is a Model Context Protocol (MCP) server that provides tools to interact with Grafana dashboards, data sources, alerts, and more. It is intended for users who want to connect AI assistants like Claude Code to a Grafana instance via the MCP standard.
Install the package from GitHub with pip install -e git+https://github.com/izaitsevfb/grafana-mcp.git#egg=grafana_mcp, then create a .env file with GRAFANA_URL and GRAFANA_API_TOKEN. Run the server with python -m grafana_mcp and add it to Claude Code using claude mcp add-json grafana with a stdio transport configuration.
It provides `get_grafana_info()`, `list_dashboards()`, `get_dashboard(uid)`, `get_organization()`, and `list_datasources()`.
Create a `.env` file with `GRAFANA_URL` and `GRAFANA_API_TOKEN`, where the API token is generated in Grafana under Configuration → API Keys.
The package requires Python, `grafana-client`, `python-dotenv`, and `mcp` (Model Context Protocol server implementation).
The test suite includes mocked tests that do not require an actual Grafana instance, but the server itself needs a valid Grafana URL and API token to function.
Use the command `claude mcp add-json grafana '{ "type": "stdio", "command": "python", "args": [ "-m", "grafana_mcp" ], "env": {} }'`. Add `--scope user` for global availability.

MCP-first toolbox for agents: namespaced key-value storage, a FIFO queue, auth, and a handful of stateless utility tools (JWT decode, hashing, cert inspection, CIDR math). Free while in early access. This repository is a

SSH MCP server for AI agents: remote commands, file transfer, log search and server audits through OpenSSH.

Routebase keeps your API's design, docs, contract tests, mocks and monitoring in one living OpenAPI spec so they can't drift apart. Agents work on that same source of truth, under your team's permissions.
Modelglass turns "which model should I use?" into a lookup instead of a guess. Seven tools give your agent live pricing across image, language, video, and audio models. Sourced and versioned, not scraped once and forgott

AI SEO tools for MCP clients — audit whether AI crawlers can read a website, validate JSON-LD and robots.txt, and generate llms.txt, AI-crawler-aware robots.txt, and JSON-LD schema without leaving the conversation.
コメント