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Blueprint Chart

Blueprint Chart

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blueprintchart.comData & Analytics0Updated 9w ago

About Blueprint Chart

Blueprint Chart is an MCP server for authoring and rendering open .bpc charts with LLMs. It provides dataviz guidance, DSL references, examples, and deterministic validation and rendering tools for an iterative authoring loop.

Key features

  1. 01Validate and inspect .bpc DSL
  2. 02Recommend chart types from data shape
  3. 03Render charts as SVG, PNG, or HTML
  4. 04Search chart examples and palettes
  5. 05Access chart guidance and grammar resources

Use cases

  1. 01Draft a chart from a natural-language request
  2. 02Check and revise .bpc syntax
  3. 03Render and export charts for sharing

MCP support

Exposes chart documentation and samples as MCP resources, plus tools for validation, inspection, recommendations, rendering, and export. An authoring prompt guides the read-write-validate-render iteration.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"blueprint-chart": {
"command": "npx",
"args": [
"-y",
"@blueprint-chart/mcp"
]
}
}
}
Run commandnpx -y @blueprint-chart/mcp

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npm@blueprint-chart/mcp0.2.1

Tools

11

Saved tool list · updated 2w ago

ParameterTypeRequiredDescription
sourcestringYesThe .bpc chart source to parse and validate.

Details

From the project README

blueprint-chart

Model Context Protocol server for authoring Blueprint Chart .bpc files with LLMs, grounded in real dataviz pedagogy with a tight parse + render feedback loop. An open, plain-text chart format an AI can write and any browser can render. Self-contained, no backend, no account required.

Status
CI checksGithub Actions
Latest versionLatest version
Release dateRelease date
Open issuesOpen issues
WebsitesEditor Docs
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The MCP exposes Blueprint Chart's dataviz handbook, DSL grammar reference, chart-type docs, and canonical samples as MCP resources, plus eleven deterministic tools: validate_dsl, inspect_dsl, recommend_chart_type, render, list_chart_types, describe_chart_type, get_example, get_grammar, export_chart, search_examples, and list_palettes. Your LLM writes the .bpc; the MCP grounds it in real dataviz pedagogy and gives it a tight feedback loop.

Install

npx @blueprint-chart/mcp           # stdio (for Claude Desktop, Claude Code, Cursor)
npx @blueprint-chart/mcp --http    # HTTP/SSE on 127.0.0.1:4321

Use with Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "blueprint-chart": {
      "command": "npx",
      "args": ["-y", "@blueprint-chart/mcp"]
    }
  }
}

Use with Claude Code

claude mcp add blueprint-chart \
  -e BLUEPRINT_CHART_EDITOR_URL=https://blueprintchart.com \
  -e BLUEPRINT_CHART_DOCS_URL=https://docs.blueprintchart.com \
  -- npx -y @blueprint-chart/mcp

Tools

ToolPurpose
validate_dslParse .bpc; returns { valid, errors[], warnings[] } — each error has code, message, suggestion
inspect_dslParse and summarize: chartType, scenes, seriesCount, rowCount, hasHighlights, hasColorizes, etc.
recommend_chart_typeRank chart types for a given column shape and row count
renderRender to SVG (default), PNG, or HTML; with format:"png" returns an inline image both you and the user can see. Always returns structured frame metadata. When MCP_PUBLIC_URL is set, includes urls ({png,svg,bpc}) — stateless links where the chart data travels inside the URL. Set modelVisible:false to drop the inline image from the response entirely, spending no image tokens. Pass save:<path> to write the output to disk (requires MCP_FS_WRITE_DIR; writes are confined to that directory). Width/height capped at 1600; PNG is 2× retina.
list_chart_typesList all renderable chart types (tool equivalent of bpc://handbook/choosing)
describe_chart_typeProperties, when-to-use, when-NOT-to-use, and data-shape for one chart type (tool equivalent of bpc://chart-types/{slug})
get_exampleFetch a canonical .bpc sample by chart type or sample name (tool equivalent of bpc://samples/{id})
search_examplesFind canonical examples by topic keywords and/or chart type (returns pointers; fetch full DSL with get_example)
get_grammarFull DSL syntax reference (tool equivalent of bpc://grammar)
list_palettesList named colour palettes with hex colours for colorPalette
export_chartValidate a .bpc and return shareable URLs plus an inline preview. Returns { copyUrl, embedUrl, urls?, frame } — copyUrl is editable in the editor, embedUrl is a read-only iframe target, urls.{png,svg,bpc} are stateless rendered/source links (when MCP_PUBLIC_URL is set). Set modelVisible:false to drop the inline preview from the response entirely, spending no image tokens. Requires BLUEPRINT_CHART_EDITOR_URL; preview failures never block the export.

The discovery tools (list_chart_types, describe_chart_type, get_example, search_examples, get_grammar, list_palettes) let clients without MCP resource support access the same reference material that the bpc:// URIs expose.

Saving rendered output

The render tool can write its output to disk via save: <path>. This is disabled by default. Set MCP_FS_WRITE_DIR to a directory to enable it — ideally an absolute path; a relative value is resolved from the server's working directory at startup. Every write lands inside that directory (a sandbox), so you never have to worry about where a client puts files: relative save paths are joined to it, an absolute path already inside it is used as-is, and any other absolute path is re-anchored under it (the leading slash is stripped and the rest joined on, so save: "/tmp/foo.png" becomes <dir>/tmp/foo.png). Only paths that still escape via ../ traversal are rejected. Missing subdirectories are created automatically. Containment is checked lexically (no realpath), so a symlink whose lexical path is inside the sandbox still passes the check and is then resolved by the OS at write time — if its target is outside the sandbox, the write reaches it. Avoid placing symlinks in the sandbox if isolation matters to you.

Add the -e flag to your claude mcp add command:

claude mcp add blueprint-chart \
  -e MCP_FS_WRITE_DIR=/path/to/output \
  -- npx -y @blueprint-chart/mcp

Resources

  • bpc://grammar — full DSL syntax reference
  • bpc://handbook/<slug> — dataviz pedagogy (choosing, design-principles, color, typography, annotations, accessibility, ...)
  • bpc://guide/<slug> — usage guides (scenes, palettes, data-transforms, ...)
  • bpc://chart-types/<slug> — per-chart-type docs
  • bpc://samples/<id> — canonical .bpc examples
  • bpc://reference/dsl/<slug>, bpc://reference/api/<slug> — full reference

Prompts

  • author_chart — primes the LLM end-to-end (read → write → validate → render → iterate)

Examples

Quickstart with Claude

Once the MCP is connected, ask Claude to make a chart:

You: Make a horizontal bar chart of English letter frequencies — top 10, highlight E.

Claude: (calls list_chart_types, get_example({ chartType: "bar-horizontal" }), writes the .bpc, calls validate_dsl to confirm it parses, calls render with format: 'png' and shows you the image and the source)

Here's the chart:

![image]

chart bar-horizontal {
  title = "E is the most frequent letter in English"
  sort = descending
  valueLabels = true
  highlight "E"
  data { "E" = 12.70; "T" = 9.06; "A" = 8.17; ... }
}

The MCP grounds Claude in real dataviz pedagogy (the handbook) before it writes a single line of DSL, then closes the loop with deterministic parse + render feedback.

What .bpc looks like
chart bar-vertical {
  title = "E is the most frequent letter in English"
  description = "How often each letter appears in typical English text"
  source = "Lewand, Cryptological Mathematics"
  colorPalette = "London"
  sort = descending
  valueLabels = true
  highlight "E"

  data {
    "E" = 12.70
    "T" = 9.06
    "A" = 8.17
    "O" = 7.51
    ...
  }
}

Full grammar at bpc://grammar; 17 canonical samples at bpc://samples/<id> (letter-frequency, co2-emissions, quarterly-revenue, browser-market, temperature-anomaly, population-stacked-bar, ...).

validate_dsl — parse with structured diagnostics

Request:

{
  "name": "validate_dsl",
  "arguments": { "source": "chart bar-vertical {\n  title = \"oops\n}" }
}

Response — valid is false; each entry in errors[] carries a code, human-readable message, and an actionable suggestion:

{
  "valid": false,
  "errors": [
    {
      "code": "E_PARSE",
      "message": "Expected \"\\\"\" but end of input found.",
      "suggestion": "Close the string literal on line 2."
    }
  ],
  "warnings": []
}
inspect_dsl — structured summary

Request:

{ "name": "inspect_dsl", "arguments": { "source": "<.bpc source>" } }

Response:

{
  "ok": true,
  "data": {
    "chartType": "bar-vertical",
    "scenes": [{ "index": 1, "hasTransition": false }],
    "hasAnnotations": false,
    "hasColorizes": false,
    "hasHighlights": true,
    "hasAreaFills": false,
    "seriesCount": 0,
    "rowCount": 26
  }
}
recommend_chart_type — ranked suggestions

Request:

{
  "name": "recommend_chart_type",
  "arguments": { "columnTypes": ["date", "number", "number", "number"], "rowCount": 24 }
}

Response:

{
  "ok": true,
  "data": {
    "recommendations": [
      { "chartType": "line-multi", "label": "Multi-Line Chart", "fitness": "best",
        "reason": "1 date + 3 numeric columns — compare trends" },
      { "chartType": "bar-multi",  "label": "Grouped Bar Chart", "fitness": "alternative",
        "reason": "Can also show as grouped bars" }
    ]
  }
}
render — SVG (default), PNG, or HTML

Request:

{
  "name": "render",
  "arguments": { "source": "<.bpc source>", "format": "png", "width": 800, "height": 500 }
}

Response:

{
  "ok": true,
  "data": {
    "svg": "<svg ...>...</svg>",
    "png": "<base64-encoded image>",
    "mimeType": "image/png",
    "urls": {
      "png": "https://mcp.blueprintchart.com/render.png?bpc64=…",
      "svg": "https://mcp.blueprintchart.com/render.svg?bpc64=…",
      "bpc": "https://mcp.blueprintchart.com/render.bpc?bpc64=…"
    }
  }
}

The urls field is only present when MCP_PUBLIC_URL is configured; every render and export_chart response then includes these stateless links, with the chart data travelling inside the URL (as bpc64, a URL-safe base64 encoding of the .bpc source) — no session, no server state required. Set modelVisible:false in the request to drop the inline image from the response entirely, spending no image tokens.

If rasterization fails (rare), errors[] is non-empty — each entry has a code ("E_RENDER") and a suggestion — and the response still includes the SVG that was successfully produced, so partial success is preserved.

Hosted render URLs

Embed a chart directly in a page:

<img src="https://<your-mcp-host>/render.png?bpc64=<bpc64value>&width=800&height=500" alt="My chart" width="800" height="500">

/render.bpc serves the raw .bpc source — it's "view source" for any chart URL, handy for sharing or reproducing a chart from its link alone.

Sources whose encoding exceeds 8 KB return 413 from the endpoints (and the tool omits urls, returning urlsOmitted: "source-too-large" instead) — use the inline PNG for very large charts.

Reading a resource
{ "uri": "bpc://handbook/choosing" }

Returns the full Markdown of the "Choosing the Right Chart" handbook page (same content as docs.blueprintchart.com).

{ "uri": "bpc://samples/letter-frequency" }

Returns the raw .bpc source for the letter-frequency sample as text/plain — exactly what the LLM should imitate.

License

MIT

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