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Works with any MCP-capable client (Claude Code, Claude Desktop, Cursor, Copilot Studio). Requi","maintainers":[{"name":"codexguy","email":"joelc@codexframework.com"}],"readme":"# @bicharts/chart-mcp (experimental)\n\n> **Make Generative AI for Charts *Better*.**\n\nAn MCP (Model Context Protocol) stdio server that puts **RegiaBI** behind any\nMCP-capable AI client (Claude Code, Claude Desktop, Copilot Studio, Cursor, …).\n\nWhat that buys you: a working, interactive chart that **fits your data on the first\ntry** — real source you commit, with no D3, Vega or charting-API expertise in the\nloop, and a solid starting point to adjust rather than a blank page. Because the\nengine knows what ~90 chart types can honestly say, it will sometimes propose a view\n— or a measure — you had not thought to ask for. Three tools:\n\n- **`assess_data_shape`** — profiles a CSV **locally** with the same measurement\n  engine the Power BI visual uses (`@bicharts/shape-core`). No backend call, no\n  credentials, no data leaves the machine. The free-teaser tool.\n- **`list_eligible_charts`** — the **authoritative** list of chart types that can\n  render this data (server-side policy, not a local guess; **no LLM**, but a network\n  call to the engine and therefore **metered** — see Credentials).\n  By default it **auto-detects the project's language** (JS/TS vs Python from the\n  working dir) and returns the charts for THAT language — **scoped to its renderers\n  and ranked by the picker's chart-type×renderer weights** (best first), each tagged\n  with its **source language** (JavaScript for D3/Vega, Python for Plotly/matplotlib),\n  its renderer, and a 0–100 score. Pass `language: \"javascript\"|\"python\"` to force it,\n  `renderer: \"D3\"/\"PLOTLY\"/…` to rank one specific renderer, or `renderer: \"\"` for the\n  full **renderer-agnostic** eligibility across all renderers (unranked — the wide \"what\n  *can* render\" net). `top: N` trims to the best N. If the language can't be auto-detected\n  and none is given, the tool asks you to specify one. **Credentials required** — no LLM\n  is not the same as no cost, because eligibility *is* the engine's own answer. Free within\n  a generous hourly allowance; beyond it a call may draw usage credits. A live licence\n  additionally unlocks *draft* types.\n- **`generate_chart`** — profiles locally, then calls the BIC backend, which picks\n  an eligible chart type for the measured shape (or honors `chart_type`) and\n  returns code that has passed the backend's gates/QC. Renderer selection is the same\n  **language-aware** intersection: with no explicit `renderer`, the detected/`language`\n  narrows the backend's auto renderer pick to that language (JS → D3/Vega, Python →\n  Plotly/matplotlib); an explicit `renderer` always wins. For D3 output, passing\n  **`preview_html: true`** alongside `out_dir` also writes a standalone `preview.html`\n  you can open with no build step. It is **off by default** — the code is meant to be\n  merged into your app, not run as an index.html.\n\n## generate_chart's machine-readable result\n\n`generate_chart` answers on two channels. The text block is for a human (and for hosts that\nonly render text); `structuredContent` is for code, so nothing has to string-parse\n`--- code ---` out of prose:\n\n| field | |\n| --- | --- |\n| `code` | the `render()` source (omitted when `include_code: false`) |\n| `chartName`, `language`, `version`, `creditCost` | what was produced, and what it cost |\n| `correlationId` | the handle into the server-side log — quote it in any support request |\n| `outputHash` | the server's identity for this exact code (the same code always carries the same hash) — keep it with the chart |\n| `requiredD3Plugins` | packages the code calls, e.g. `[\"d3-sankey\"]` — install them and pass the host **one** d3 that carries them, built with `assembleD3(d3, { ...plugins })` from `@bicharts/chart-host` (assigning onto an ES-module `d3` namespace throws), or the chart throws mid-render |\n| `geo` / `geoPoint` | region/basemap wiring, and how many points actually placed |\n| `geoPointDest` | present only for a route (an origin-destination flow map): the same count for each row's destination, which is geocoded apart from the origin |\n| `data` **or** `files` | the render payload inline, **or** the paths written — never both |\n| `hostContract`, `build` | the contract the code targets, and the bundle that served the call |\n| `recoveredAfterMs` | present only when the response stream was cut and the chart was fetched back by its correlation: milliseconds from the start of the call to delivery. `creditCost` is null then |\n\n`data` carries the appended `__geoIso__` / `__geoLat__` / `__geoLon__` columns (and a route's\n`__geoLatD__` / `__geoLonD__`), which a caller\ncannot reconstruct from the source data — so a geo chart needs either it or `files.data`.\n\n## Language & renderer\n\nBoth list/generate tools speak **language** (what your project is written in) as well as\n**renderer** (a specific chart library). The server maps `javascript`/`typescript` → D3 +\nVega and `python` → Plotly + matplotlib, and the picker's weights rank across that\nlanguage's renderers. Precedence is **explicit `renderer` > `language` > auto-detected\nlanguage**. The MCP sniffs the working directory (or `project_dir`) for language markers\n(`package.json`/`tsconfig.json` → JS, `pyproject.toml`/`requirements.txt` → Python) plus a\nbounded source-file count; when the signal is genuinely mixed or absent it asks you to\npick rather than silently assuming one.\n\n## Data inputs — CSV or a pre-typed table\n\nBoth tools accept, as alternatives:\n\n- `csv_path` / `csv_text` — a CSV; column types and measure/dimension roles are\n  **inferred** (numeric-non-identifier = measure), and you can steer them with the\n  `measures`/`dimensions`/`formats`/`descriptions` levers.\n- `data: { columns, rows }` — a **pre-typed table**, the shape a **Fabric DAX\n  Execute-Queries result**, a dataframe, or an arrow table already has. `columns`\n  carry `name` and (optionally) `dataType`, `isMeasure`, `format`, `description`;\n  `rows` are positional arrays **or** objects keyed by column name. When a caller\n  supplies `isMeasure` + `format` + `description` from a semantic model, the shape\n  matches Power BI fidelity with **no heuristic guessing** — the profiler engine\n  is the same one the visual runs; CSV was only ever one adapter over it.\n\nExample (a semantic-model query result):\n\n```json\n{\n  \"data\": {\n    \"columns\": [\n      { \"name\": \"Region\",  \"dataType\": \"String\",  \"isMeasure\": false },\n      { \"name\": \"Revenue\", \"dataType\": \"Decimal\", \"isMeasure\": true,\n        \"format\": \"$#,##0\", \"description\": \"Net booked revenue\" }\n    ],\n    \"rows\": [ { \"Region\": \"West\", \"Revenue\": 12000.5 }, { \"Region\": \"East\", \"Revenue\": 9000 } ]\n  }\n}\n```\n\n## Build\n\n```powershell\ncd mcp\nnpm install\nnpm run build     # bundles to dist/index.mjs (single file)\n```\n\n## Credentials (`generate_chart` and `list_eligible_charts`)\n\n**A trial or paid BIC account is required — no freemium.** Use the same\n**License Key**, **Licensee**, and **Secret Key** from your BIC account (the ones\nthe Power BI visual's license settings use).\n\n`assess_data_shape` needs no credentials at all — it runs entirely locally in\n`@bicharts/shape-core` and never calls the backend. `list_eligible_charts` **does**\nneed them: it is the server's own eligibility verdict, not a local guess, which is\nthe whole reason it is worth calling. It is free within a generous hourly allowance;\nbeyond that, a call may draw usage credits from the account (both knobs are\nserver-configured), so don't put it inside a tight loop. Use of the API and this MCP\nserver is covered by the\n[RegiaBI Programmatic Access Terms](https://bizintelligencechampions.com/terms-regiabi).\n\nTwo ways to supply them — env wins over the file:\n\n**1. Env vars** (via the MCP server's `env` block — see registration below):\n\n| Var | Meaning |\n| --- | --- |\n| `BIC_LICENSE_KEY` | required |\n| `BIC_LICENSEE` | required (account name) |\n| `BIC_SECRET_KEY` | optional |\n| `BIC_URL` | override backend (default `https://bizintelligencechampions.com`) |\n| `BIC_MCP_REASONING` | OPTIONAL override of the default reasoning mode (else `\"\"` = leave-to-visual, same as the PBI visual) |\n| `BIC_MCP_MODEL` | OPTIONAL override of the default model (else `\"\"` = the account's IsDefault model, same as the visual) |\n| `BIC_MCP_TIMEOUT_MS` | OPTIONAL: how long one `generate_chart` call waits, recovery included (default `900000`, 15 minutes) |\n\n**Defaults match the Power BI visual.** Unset, the MCP sends `model=\"\"` (server\nresolves the `IsDefault` model), `reasoning_mode=\"\"` (leave-to-visual heuristic), and\n`privacy_level=\"20\"` (detailed stats, **no sample rows** — see below). The two env\nvars above are escape hatches only; leave them unset for visual parity.\n\n### Response timeouts (HTTP 499 / dropped connection)\n\nThe backend completes long multi-pass generations (the visual regularly runs several\nminutes on rich charts). A dropped connection is therefore a **delivery timeout in\nthe calling path** — the MCP host's tool-call timeout or an intermediary proxy — not\na server ceiling, and not a generation failure (the chart likely generated and may\nhave been billed). The parity-preserving fix is to **let the call take as long as it\nneeds**:\n\n- **Built in:** the server sends MCP progress notifications every 10s during a\n  generation; spec-compliant hosts (including Claude Code) reset their per-call\n  timeout on progress, so the call stays alive as long as the generation needs —\n  no user configuration required.\n- Fallback for hosts that don't reset on progress: raise the host's per-tool\n  timeout (Claude Code: `MCP_TOOL_TIMEOUT` in ms, set in the environment Claude\n  Code itself runs in — e.g. the `env` block of `settings.json`).\n- **Built in:** when the response stream is cut *after* the server accepted the\n  request, the MCP does not give up or re-generate. Inside the same tool call it\n  checks for the finished chart by its `correlationId` (a fetch that can never call a\n  model), backing off between checks, until the chart arrives or the recovery window\n  or `BIC_MCP_TIMEOUT_MS` runs out, whichever is sooner. A recovered chart carries\n  `recoveredAfterMs`; when nothing arrives, the error keeps the `correlationId` to\n  quote to support.\n\n`BIC_MCP_REASONING=CP`/`1P` *would* finish faster, but that trades away visual parity\n(no validator) — prefer raising the timeout.\n\n**2. A credentials file** — so secrets never sit in a project-committed\n`.mcp.json`. Default `~/.bic/credentials.json` (override with\n`BIC_CREDENTIALS_FILE`):\n\n```json\n{ \"licenseKey\": \"…\", \"licensee\": \"…\" }\n```\n\n(`secretKey` optional.)\n\nPrefer the file, or a **user-scoped** `claude mcp add` (stored in your user\nconfig), over putting secrets in a repo-committed `.mcp.json`.\n\nNote: this package deliberately does NOT contain the freemium key-mint secret —\nconsistent with trial/paid-only access, and safe if the folder is ever published.\n\n### Credit charges\n\nEach `generate_chart` call spends credits on your account, exactly like the Power BI\nvisual (the MCP hits the same billed endpoint):\n\n- **Hosted** (our models) → **token-based** — you pay for the tokens the generation\n  actually used.\n- **BYO** (your own API key) → a **flat operating fee per request**, priced for\n  this surface separately from the Power BI visual. Current rates are shown in your\n  account.\n\nThe response header line shows `credits: N` so you can see what each call cost.\n\n## The agent skill (recommended)\n\nThis package ships `skills/bic-charts/SKILL.md` — the golden path from empty directory to a\nworking cross-filtered dashboard: the scaffold command block, when to use the authoritative\ncontract parameters instead of `prompt` prose, the coordinated-dashboard recipe, and the\nhandful of places builds measurably lose time. Copy it where your agent looks for skills:\n\n```powershell\nmkdir -Force .claude\\skills\nCopy-Item -Recurse (npm root)\\@bicharts\\chart-mcp\\skills\\bic-charts .claude\\skills\\\n```\n\nAn agent that reads it first does in a few calls what otherwise takes thirty — most of the\ndifference is not knowing the API, it is not knowing the shape of the answer.\n\n## Register with Claude Code\n\n```powershell\nclaude mcp add --scope user bic-chart -- npx -y @bicharts/chart-mcp\n```\n\n`--scope user` stores it in your user config so it works in every project. With\ncredentials in `~/.bic/credentials.json` you need no `-e` flags at all; add them only\nif you prefer env vars:\n\n```powershell\nclaude mcp add --scope user bic-chart -e BIC_LICENSE_KEY=... -e BIC_LICENSEE=... -- npx -y @bicharts/chart-mcp\n```\n\nor in a project `.mcp.json`:\n\n```json\n{\n  \"mcpServers\": {\n    \"bic-chart\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"@bicharts/chart-mcp\"]\n    }\n  }\n}\n```\n\nClaude Desktop uses the same `command`/`args`/`env` block in\n`claude_desktop_config.json` under `mcpServers`.\n\n**Developing on the server itself?** Point at your build instead, so you are not\nrunning whatever npx last cached:\n\n```powershell\nclaude mcp add --scope user bic-chart-dev -- node c:/Source/PowerBI_Controls/llmchart/mcp/dist/index.mjs\n```\n\nThe ready banner prints the build stamp, which is how you tell the two apart.\n\nTry: *\"Assess the shape of testharness/datasets/divisional_revenue_by_year.csv,\nthen generate a chart for it and write the preview to ./out.\"*\n\n## Wire notes\n\nWire-compatible with the visual/harness envelope (see\n`testharness/harness/client.py`, the reference implementation): gzip→base64→`.`\nbody, FNV X-Signature, `clientVersion >= 2.0.0.0`, plus `host: \"SDK\"` so prompts\nresolve to the generic host profile once server rev 144 + tokenized config are\nlive (older servers ignore the field — deployment-order safe).\n\n## Publishing (when the experiment proves out — NOT yet)\n\n1. Keep `\"private\": true` until the conscious decision to release.\n2. Publish **built artifacts only** (`files: [\"dist\"]` already enforces this —\n   the tarball carries the bundled `dist/index.mjs`, no source, no history).\n3. `npm publish --access public` under the org scope; users then configure\n   `\"command\": \"npx\", \"args\": [\"-y\", \"@bicharts/chart-mcp\"]` — zero-install.\n4. List in MCP registries/directories for discoverability.\n5. shape-core rides inside the bundle minified (shared, not shown); the\n   open-source decision for readable source is separate and deferred.\n","readmeFilename":"README.md"}