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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".

DeepseekModel 官方收录技能 质量 优秀 · 78 v1.0.0

获取

https://deepseekmodel.com/api/download.php?id=grafana-skills-skills-grafana-cloud-assistant-mcp-skill-md&format=skill
下载 .skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
name assistant-mcp license Apache-2.0 description 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". 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) # 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. 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 ). Wire ~/.claude/settings.json (or project-local .claude/settings.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. 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 ): { "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 Grafana MCP server (github.com/grafana/mcp-grafana) Model Context Protocol specification Grafana Cloud API documentation Grafana Assistant documentation
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下载的 .skill 包内含以下字段。
字段 说明
format格式标识(skill/v1)
skill_id技能唯一 ID
name技能名称
version版本号
description技能描述
category所属分类(数组)
trigger_words触发词列表
tags标签列表
source来源标识
source_url来源链接(本页地址)
exported_at导出时间(每次下载生成)
system_prompt系统提示词正文
model_config模型参数:provider / model / temperature / max_tokens / top_p
examples示例
install_guide各平台导入说明(Coze / Dify / Claude / 自定义框架)
同一份技能可按不同平台格式导出。
.skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用 下载
.skillpro 增强格式,额外含脚本 / 工具 / 依赖 / 钩子占位 下载
.json 纯 JSON 导出,只含 system_prompt 与模型参数 下载
Coze 带 frontmatter 的 Markdown,Coze 平台导入用 下载
Dify Dify DSL,创建应用后直接导入 下载

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