Assistant Mcp logo

Assistant Mcp

Organization
grafana
assistant-mcp

Connect AI coding agents (Claude Code, Cursor, VS Code, OpenAI Codex) to Grafana Cloud via the `mcp-grafana` Model Context Protocol server. Installs the server with `go install`, generates a Grafana service-account token, wires `~/.claude/settings.json` or `~/.cursor/mcp.json` with the `command` + `env` block, runs `--disable-write` for safer read-only sessions, switches to SSE transport for team-shared / VS Code setups, and verifies with `/mcp` + a `list_datasources` round-trip. Use when connecting Claude Code to Grafana, setting up MCP for Grafana, configuring the Grafana MCP server, using Grafana tools in Cursor/VS Code, querying Grafana from an AI agent, sharing the MCP server across a team — even when the user says "give my agent Grafana access", "let Claude see my metrics", or "Cursor + Grafana" without saying "MCP".

Overview

Publishergrafana
Repositoryskills
Skill nameassistant-mcp
Stars
289
Forks
27
Bundled files
3
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by grafana on GitHub. Read the source before you install it.

Installation

Install the Assistant Mcp AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/grafana/skills/tree/main/skills/grafana-cloud/assistant-mcp
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/grafana/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/grafana-cloud/assistant-mcp .claude/skills/assistant-mcp
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Assistant Mcp in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Assistant Mcp on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Assistant Mcp is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Grafana Cloud MCP Server Setup

The Grafana MCP server exposes Grafana Cloud capabilities as tools that AI agents can call via the Model Context Protocol. Agents can then query metrics, search dashboards, manage alerts, investigate incidents, and interact with Fleet Management without leaving the coding environment.

Transports: stdio (agent spawns the server as a subprocess, simplest), or SSE (server runs independently, agents connect via HTTP — see references/sse-transport.md).

Common Workflows

Connecting Claude Code to Grafana (stdio)

bash
# 1. Install the server
go install github.com/grafana/mcp-grafana/cmd/mcp-grafana@latest

# 2. Verify the binary
mcp-grafana --version
# If "command not found": ensure $GOPATH/bin (or $HOME/go/bin) is on PATH.
  1. Get a service-account token: Grafana Cloud → Administration → Service Accounts → create with Viewer role (add Editor only if you need writes) → generate token. Note the Grafana URL (e.g. https://myorg.grafana.net).

  2. Wire ~/.claude/settings.json (or project-local .claude/settings.json):

    json
    {
      "mcpServers": {
        "grafana": {
          "command": "mcp-grafana",
          "args": ["--disable-write"],
          "env": {
            "GRAFANA_URL": "https://myorg.grafana.net",
            "GRAFANA_API_KEY": "glsa_xxxx"
          }
        }
      }
    }

    --disable-write is the safer default — drop it once you've verified the read path works.

  3. Restart Claude Code, then verify:

    /mcp

    The grafana server should appear with its tool list. Then ask:

    What data sources are configured in my Grafana instance?

    A clean response = working. If the tool call fails:

    • Check GRAFANA_URL has no trailing slash
    • Confirm the API key hasn't expired
    • Re-run with mcp-grafana --debug to see raw request/response

Connecting Cursor

Same Grafana token. Settings → Features → MCP Servers (or edit ~/.cursor/mcp.json):

json
{
  "mcpServers": {
    "grafana": {
      "command": "mcp-grafana",
      "args": ["--disable-write"],
      "env": {
        "GRAFANA_URL": "https://myorg.grafana.net",
        "GRAFANA_API_KEY": "glsa_xxxx"
      }
    }
  }
}

Verify the same way — Cursor surfaces MCP servers in its agent panel; run a query like "list dashboards tagged kubernetes".

Sharing the server across a team (SSE)

Switch from stdio to SSE so the server runs once and many agents connect to it. Full setup with VS Code config in references/sse-transport.md.

Security considerations

  • API keys belong in env vars or a secrets manager — never in committed files.
  • Use --disable-write for shared environments and CI; only lift it on the specific machine where the agent should be allowed to mutate Grafana.
  • Scope service-account permissions to the minimum: Viewer is enough for queries and dashboard reads. Only grant Editor when the agent needs to create dashboards or annotations.
  • Rotate tokens periodically via Administration → Service Accounts.

References

  • references/tools.md — full list of MCP tools exposed (query / dashboard / alerting / Fleet Management / annotations) and how to discover the live set
  • references/sse-transport.md — SSE setup for team sharing and VS Code, with stdio-vs-SSE decision matrix + common failure modes
  • references/a2a.md — Agent-to-Agent (A2A) protocol for delegating reasoning to the Grafana Assistant (vs direct tool calls via MCP)

External resources

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Assistant Mcp AI skill do?

Connect AI coding agents (Claude Code, Cursor, VS Code, OpenAI Codex) to Grafana Cloud via the `mcp-grafana` Model Context Protocol server. Installs the server with `go install`, generates a Grafana service-account token, wires `~/.claude/settings.json` or `~/.cursor/mcp.json` with the `command` + `env` block, runs `--disable-write` for safer read-only sessions, switches to SSE transport for team-shared / VS Code setups, and verifies with `/mcp` + a `list_datasources` round-trip. Use when connecting Claude Code to Grafana, setting up MCP for Grafana, configuring the Grafana MCP server, usin...

Why use Assistant Mcp on TypingMind?

Because you install it once and use it with any model. Assistant Mcp is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Assistant Mcp in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/grafana/skills/tree/main/skills/grafana-cloud/assistant-mcp. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Assistant Mcp?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Assistant Mcp?

As many as you like. As long as a model supports skills, you can use Assistant Mcp with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Assistant Mcp AI skill free?

Yes. It is published on GitHub by grafana under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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