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V S","license":"MIT","homepage":"https://microcharts.dev/docs/mcp","keywords":["ai","ai-sdk","charts","llm","mcp","microcharts","model-context-protocol","sparkline","svg"],"repository":{"type":"git","url":"git+https://github.com/ganapativs/microcharts.git","directory":"packages/mcp"},"description":"MCP server + Vercel AI-SDK tools for microcharts — let a model find, wire, and render word-sized charts.","maintainers":[{"name":"ganapativs","email":"vsg.inbox@gmail.com"}],"readme":"# @microcharts/mcp\n\n[![microcharts MCP server](https://glama.ai/mcp/servers/ganapativs/microcharts/badges/score.svg)](https://glama.ai/mcp/servers/ganapativs/microcharts)\n\nAn MCP server and Vercel AI-SDK toolset for [microcharts](https://microcharts.dev) — let a model **find** the right\nword-sized chart, **get** exactly how to wire it, and **render** it to a finished SVG with real alt text.\n\nmicrocharts is built so a model can _write_ charts. This is how a model _calls_ them: not \"emit some grammar and hope\nthe client renders it,\" but a tool call that returns the real library's static SVG, honest by construction, with the\ngenerated `describeSeries` accessible name attached.\n\n- **Runs on your machine.** stdio server, distributed on npm. Nothing is hosted; no account, no key, no data leaves.\n- **Works anywhere.** The render tool returns self-contained SVG, so a chat surface that can't run React can still show\n  a real chart.\n- **Zero setup.** `npx @microcharts/mcp` — the package brings its own copy of `@microcharts/react`.\n\n## Install\n\nAdd it to any MCP client. For **Claude Desktop** (`claude_desktop_config.json`) or **Cursor** (`.cursor/mcp.json`):\n\n```json\n{\n  \"mcpServers\": {\n    \"microcharts\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"@microcharts/mcp\"]\n    }\n  }\n}\n```\n\nThat's it — the client spawns the server over stdio on demand.\n\n## Tools\n\n### `find_microchart(question, dataShape?)`\n\nRank the catalog against a plain-language question. Start here when you know the question, not the chart.\n\n```\nfind_microchart({ question: \"is it trending?\" })\n→ [{ slug: \"sparkline\", name: \"Sparkline\", why: \"inline trend\", dataShape: \"number[]\" }, …]\n```\n\n### `get_microchart(slug)`\n\nEverything needed to wire one chart: import paths, its props plus the shared props, data shape, best/avoid guidance, a\ncopy-runnable example, and `sample` — that same example as JSON props, ready to pass straight to `render_microchart`.\n\n```\nget_microchart({ slug: \"bullet\" })\n→ {\n    staticImport: \"@microcharts/react/bullet\",\n    props: [...],\n    example: { code: \"<Bullet value={72} target={80} bands={[50, 90]} title=\\\"Quota\\\" />\" },\n    sample: { value: 72, target: 80, bands: [50, 90], title: \"Quota\" },\n    …\n  }\n```\n\nEvery chart takes its own data shape — `number[]` for a sparkline, `{ label, value }[]` for a dot plot,\n`{ open, high, low, close }[]` for OHLC — so `sample` is the shortest path from \"which chart\" to \"a render that works\".\n\n### `render_microchart(type, data?, props?, format?)`\n\nRender to a finished, self-contained SVG plus its generated alt text. Pass the series as `data`; put other props\n(`value`, `target`, `curve`, `color`, `width`) in `props`.\n\n```\nrender_microchart({ type: \"sparkline\", data: [132, 148, 141, 165, 159, 182] })\n→ {\n    svg: \"<svg …><style>…</style>…</svg>\",\n    summary: \"Trending up 38%. Range 132 to 182. Last value 182.\",\n    mimeType: \"image/svg+xml\", width: 80, height: 20\n  }\n```\n\n`format` is `\"svg\"` (default, styles embedded — drops into any surface) or `\"bare\"` (no CSS, for pages that already load\n`@microcharts/react/styles.css`).\n\nMissing or wrong-shaped data is rejected by name rather than passed through to React, so a caller gets\n`\"dot-plot\" needs \\`data\\`. Data shape: { label, value }[]. Call get_microchart(\"dot-plot\") for a ready-to-render\nsample.` instead of a stack trace. Oversized payloads are refused too — a microchart is a word-sized mark.\n\nIt also exposes two resources: `microcharts://catalog` (every chart + metadata) and `microcharts://agent-setup` (the\nprompt for wiring microcharts into a codebase).\n\n## Use it from the Vercel AI SDK\n\nThe same three capabilities ship as AI-SDK tools (on the `/ai-sdk` subpath, so the core never pulls in `ai`):\n\n```ts\nimport { microchartsTools } from \"@microcharts/mcp/ai-sdk\";\nimport { streamText } from \"ai\";\n\nconst result = streamText({\n  model,\n  tools: microchartsTools,\n  prompt: \"Summarise this quarter and show the revenue trend as a chart.\",\n});\n```\n\nThe functions are exported directly too — `findChart`, `getChart`, `renderChart` — if you want them without the tool\nwrapper.\n\n## Versioning\n\nThis server bundles the chart catalog and renders with `@microcharts/react` (installed as a normal dependency). Its\nversion tracks its own changes; a compatible library is pulled in automatically. The library version a given snapshot\nwas cut from is on the `microcharts://catalog` resource.\n\n## Links\n\n- Docs: <https://microcharts.dev/docs/mcp>\n- Library: [`@microcharts/react`](https://www.npmjs.com/package/@microcharts/react)\n- Source: <https://github.com/ganapativs/microcharts/tree/main/packages/mcp>\n\nMIT\n","readmeFilename":""}