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highchart-mcp-server

highchart-mcp-server

by hasnaintypes

Highcharts MCP Server

A Model Context Protocol (MCP) server that turns structured input or raw Highcharts options into validated chart configurations and rendered images (SVG / PNG / PDF). It works with any MCP-capable client (Claude Desktop, Cursor, VS Code, etc.) over STDIO or Streamable HTTP.

Status: actively developed. Chart generation, rendering/export, discovery, metrics, auth + rate limiting (HTTP), and Docker packaging are implemented and tested. The server/CLI and both SDKs are published (see Packages).

Packages

Package

Registry

Install

@highchart-mcp/server

npm

npm install -g @highchart-mcp/server (provides the highchart-mcp CLI + server)

@highchart-mcp/sdk

npm

npm install @highchart-mcp/sdk

highchart-mcp-sdk

PyPI

pip install highchart-mcp-sdk

Related MCP server: mcp-highcharts

Features

  • All 70 Highcharts 12.x series types — cartesian, pie/funnel, bubble, financial (candlestick/OHLC, stockChart), heatmap/tilemap, treemap/sunburst, sankey/networkgraph/organization, gauges, boxplot/statistical, xrange/timeline, maps (mapChart), and gantt (ganttChart).

  • Two-tier tools — a guided create_chart plus raw passthrough render_chart / export_chart for full Highcharts control.

  • Discovery — list_chart_types returns every type grouped by family with data-shape hints and examples.

  • Rendering to SVG / PNG / PDF via highcharts-export-server (headless Chromium), with the correct constructor selected automatically.

  • Zod v4 validation with clear, per-type error messages.

  • Production hardening — export timeouts, configurable worker pool, request body limits, and per-session HTTP transport management.

  • Security (HTTP) — API-key or HS256-JWT auth with scopes, and token-bucket rate limiting.

  • Observability — GET /health and Prometheus GET /metrics.

  • Docker image that bakes the Highcharts script cache offline (no CDN needed at runtime).

Tools

Tool

Purpose

create_chart

Build a Highcharts config from structured input for any supported type. Returns { constr, options }, or a rendered image when format is given.

render_chart

Render a full Highcharts options object (any type). Returns config + rendered output.

export_chart

Like render_chart with format (svg/png/pdf) plus width/height/scale and constr overrides.

list_chart_types

List every supported chart type grouped by family, with data shapes and examples.

Install

Requires Node.js 22+.

From npm (published package — no clone needed):

npm install -g @highchart-mcp/server
highchart-mcp serve --transport stdio   # or: highchart-mcp serve --transport http --port 3000

From source (for development or Docker packaging):

npm ci
npm run build
npm start

Usage

Local (STDIO) — desktop AI clients

mcp.json (or Claude Desktop / Cursor config):

{
  "mcpServers": {
    "highchart-mcp-server": {
      "command": "node",
      "args": ["/absolute/path/to/highchart-mcp-server/dist/index.js"],
      "env": { "TRANSPORT": "stdio", "LOG_LEVEL": "info" }
    }
  }
}

Networked (Streamable HTTP)

TRANSPORT=http PORT=3000 node dist/index.js
# MCP endpoint: POST http://localhost:3000/mcp
# Health:       GET  http://localhost:3000/health
# Metrics:      GET  http://localhost:3000/metrics

Enable auth + rate limiting for any network exposure (see below).

Example: create_chart

{
  "type": "line",
  "title": "Monthly Sales",
  "xAxisCategories": ["Jan", "Feb", "Mar"],
  "series": [{ "name": "Revenue", "data": [10, 20, 15] }]
}

Call list_chart_types to discover the expected data shape for any type (e.g. financial [x, open, high, low, close], heatmap [x, y, value], sankey { from, to, weight }, gantt tasks[], maps topology + data).

Rendering (offline)

Rendering uses highcharts-export-server (headless Chromium), which fetches Highcharts scripts from a CDN on first run and caches them. To work offline, the scripts are sourced from the installed highcharts package:

npm run seed:cache      # populate the cache from the local package (no network)
npm run render:samples  # render one SVG per constructor to .render-samples/

The Docker image bakes this cache at build time.

Configuration

All configuration is via environment variables — see .env.example. Highlights:

Area

Variables

Transport

TRANSPORT (stdio/http), PORT, LOG_LEVEL

Rendering

EXPORT_TIMEOUT_MS, EXPORT_MAX_WORKERS, PUPPETEER_ARGS, HIGHCHARTS_CDN_URL, HIGHCHARTS_CACHE_PATH

HTTP limits

HTTP_MAX_BODY_BYTES, HTTP_MAX_SESSIONS

Auth

AUTH_STRATEGY (none/apikey/jwt/oauth), API_KEYS, JWT_SECRET, JWT_ISSUER, JWT_AUDIENCE, AUTH_REQUIRED_SCOPES, PUBLIC_URL, OAUTH_ACCESS_TOKEN_TTL_MS, OAUTH_CODE_TTL_MS, GITHUB_CLIENT_ID, GITHUB_CLIENT_SECRET, GITHUB_ALLOWED_USERS, GITHUB_ALLOWED_ORGS, OAUTH_GRANTED_SCOPES

Rate limit

RATE_LIMIT_ENABLED, RATE_LIMIT_RPM, RATE_LIMIT_BURST

Metrics

METRICS_ENABLED, METRICS_PUBLIC, METRICS_LOG_INTERVAL_MS

Licensing

HIGHCHARTS_LICENSE_ID, HIGHCHARTS_CREDITS_ENABLED (see LICENSING.md)

Deployment

Docker:

docker build -t highchart-mcp-server .
docker run -p 3000:3000 -e AUTH_STRATEGY=apikey -e API_KEYS=client1:changeme \
  --shm-size=512m highchart-mcp-server
# or: docker compose -f docker/docker-compose.yml up --build

Always enable auth + rate limiting for any network exposure and terminate TLS at a reverse proxy or the platform's load balancer.

Connecting from Claude.ai / ChatGPT (remote MCP connectors)

Claude.ai's and ChatGPT's "custom connector" UIs can't accept a pasted bearer token — they only know how to drive an OAuth 2.1 authorization-code + PKCE flow with dynamic client registration (per the MCP Authorization spec). Set AUTH_STRATEGY=oauth to have this server act as both the authorization server and resource server for that flow, with sign-in delegated to GitHub — no passwords or credential database to manage:

AUTH_STRATEGY=oauth PUBLIC_URL=https://mcp.highcharts-mcp.site \
  GITHUB_CLIENT_ID=... GITHUB_CLIENT_SECRET=...
  • PUBLIC_URL must be the externally-reachable HTTPS origin of this server (no trailing slash) — it's used as the OAuth issuer/audience and in the .well-known discovery documents, since the process can't infer it behind a reverse proxy.

  • Create a GitHub OAuth App with Authorization callback URL set to ${PUBLIC_URL}/oauth/github/callback, then set GITHUB_CLIENT_ID/GITHUB_CLIENT_SECRET from it. When a platform starts the OAuth flow, GET /authorize redirects the user's browser straight to GitHub to sign in — no form, no shared secret to distribute.

  • By default any GitHub account may connect. Restrict access with GITHUB_ALLOWED_USERS (comma-separated usernames) and/or GITHUB_ALLOWED_ORGS (comma-separated org logins the user must belong to).

  • Every authorized GitHub identity is granted the scopes in OAUTH_GRANTED_SCOPES (comma-separated) — set this to cover AUTH_REQUIRED_SCOPES if you use scope enforcement, since GitHub identity itself carries no app-specific scopes.

  • No extra dependency or database is required: client registrations, authorization codes, pending sign-ins, and refresh tokens are held in-process (see src/auth/oauth/store.ts), the same tradeoff already made for HTTP sessions and rate limiting — fine for a single-instance deployment.

  • In Claude.ai, add a Custom Connector pointing at https://mcp.highcharts-mcp.site/mcp; in ChatGPT, add it as an MCP connector with the same URL. Both will discover /.well-known/oauth-protected-resource, self-register via /register, and redirect the user through /authorize → GitHub sign-in automatically.

CLI

The build installs a highchart-mcp CLI (bin → dist/cli/index.js):

highchart-mcp list-types                 # list all types grouped by family
highchart-mcp list-types --family maps --json
echo '{"series":[{"data":[1,2,3]}]}' | highchart-mcp create --type line --input -
highchart-mcp create --type line --input chart.json --format svg --out chart.svg
highchart-mcp render --input options.json --format png --out chart.png
highchart-mcp export --input options.json --format pdf --width 1000 --out chart.pdf
highchart-mcp serve --transport http --port 3000

render/export require a seeded render cache (npm run seed:cache) or network.

SDKs

Published client libraries (source in packages/, in-repo npm workspaces):

  • JS/TS: @highchart-mcp/sdk (source)

    npm install @highchart-mcp/sdk
    import { HighchartClient } from '@highchart-mcp/sdk';
    const client = await HighchartClient.connectHttp('https://mcp.highcharts-mcp.site/mcp', { apiKey });
    const { options } = await client.createChart({ type: 'line', series: [{ data: [1, 2, 3] }] });
  • Python: highchart-mcp-sdk (source)

    pip install highchart-mcp-sdk
    async with HighchartClient.connect_stdio(command="node", args=["dist/index.js"]) as client:
        cfg = await client.create_chart(type="line", series=[{"data": [1, 2, 3]}])

Development

npm run dev    # tsx --watch src/index.ts
npm run build  # tsc (server + CLI)
npm test       # vitest run (server + CLI)

npm run build --workspace @highchart-mcp/sdk   # build the JS/TS SDK
npm test  --workspace @highchart-mcp/sdk       # test the JS/TS SDK

Contributing

Contributions welcome — see CONTRIBUTING.md for dev setup, PR expectations, and code style. Issues labeled good first issue are a good place to start; help wanted issues are open and unclaimed.

Versioning & Publishing

All three published packages are versioned independently with semver, each in its own package.json / pyproject.toml:

Package

Version file

@highchart-mcp/server

package.json

@highchart-mcp/sdk

packages/sdk-js/package.json

highchart-mcp-sdk

packages/sdk-python/pyproject.toml

Rule: bump the version of every package you change before publishing — never publish the same version twice. Patch (x.y.Z) for fixes, minor (x.Y.0) for backwards-compatible features/additions, major (X.0.0) for breaking changes. A change to src/** bumps @highchart-mcp/server; a change to packages/sdk-js/** bumps @highchart-mcp/sdk; a change to packages/sdk-python/** bumps highchart-mcp-sdk. Shared/cross-cutting changes (e.g. a protocol change affecting the tools) bump all affected packages together.

Automated (CI) — the normal path

.github/workflows/publish.yml publishes automatically on every push to master. For each package it compares the version in the repo against the version currently on the registry; if it's different, it builds, tests, and publishes that package (and only that one). So publishing a new version is just:

  1. Bump the version(s) that changed (see the rule above).

  2. Commit and push/merge to master.

  3. CI builds, tests, and publishes automatically — no local npm publish / twine upload, no tokens to manage. It uses npm and PyPI trusted publishing (OIDC), so nothing is stored as a GitHub secret.

One-time setup (do this once per package; repeat only if the workflow file is renamed/moved, or for a new package):

  • npmjs.com → package Settings → Publishing access → Trusted Publisher, add this GitHub repo + .github/workflows/publish.yml — for both @highchart-mcp/server and @highchart-mcp/sdk.

  • pypi.org → project Settings → Publishing, add this GitHub repo + .github/workflows/publish.yml — for highchart-mcp-sdk.

You can also trigger it manually from the Actions tab (workflow_dispatch) if you need to re-run a publish without a new push.

Manual (fallback)

If CI is down or you need to publish from your machine:

# 1. Bump the version(s) that changed, build, and test.
npm version <patch|minor|major> --no-git-tag-version        # root package
npm version <patch|minor|major> --no-git-tag-version -w @highchart-mcp/sdk
# packages/sdk-python/pyproject.toml: bump `version = "..."` by hand

npm run build && npm test
npm run build -w @highchart-mcp/sdk && npm test -w @highchart-mcp/sdk

# 2. Publish (npm requires an OTP if 2FA is enabled).
npm publish --access public --otp=<code>
npm publish -w @highchart-mcp/sdk --access public --otp=<code>

# 3. Publish the Python SDK.
cd packages/sdk-python
rm -rf dist && python -m build
twine check dist/*
twine upload dist/*   # __token__ / a PyPI API token

Commit the version bump(s) (e.g. chore(release): @highchart-mcp/server@1.1.0) alongside or right after the code change that motivated them.

Licensing

This wrapper is under the license in package.json. Highcharts itself is proprietary: free for non-commercial use with the credit attribution kept on (the default here), and requires a paid license for commercial/production use. See LICENSING.md.

Roadmap

  • Done: full chart-type coverage, rendering/export, discovery, offline cache, metrics/health, HTTP auth + rate limiting, per-session transport, robustness limits, Docker + CI, CLI + JS/TS & Python SDKs, MCP image content for svg/png renders.

  • Next — candidate ideas, not implemented: natural-language → chart config, AI chart-type suggestions/auto-correction, dashboards/batch export. See docs/roadmap.md for the full list.

Available Tools

2 tools
create_chartB

Generate a Highcharts configuration object from structured input. Returns valid Highcharts JSON that can be rendered in any Highcharts-compatible environment.

Inputs: type (required), series (required), title, xAxisCategories.

render_chartA

Render a chart from a full Highcharts configuration object. Accepts any valid Highcharts Options — the server validates structure (chart.type, series) but passes all other options through to Highcharts.

Inputs: chartOptions (required).

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

    TDQS

    A3.7/5.0

    Scored across 2 tools

    Disambiguation5/5

    The two tools have clearly distinct purposes: create_chart generates a Highcharts configuration object, while render_chart takes a full configuration and renders it. No overlap or ambiguity exists.

    Naming Consistency5/5

    Both tool names follow a consistent verb_noun pattern (create_chart, render_chart) in snake_case, making them predictable and easy to understand.

    Tool Count3/5

    With only 2 tools, the server is minimal. While it covers core chart creation and rendering, it feels thin for a full-featured charting service, potentially missing operations like listing or managing chart configurations.

    Completeness4/5

    The server covers the essential lifecycle of generating and rendering a chart configuration. Minor gaps exist, such as lacking update or delete operations, but the domain is straightforward and the provided tools suffice for basic use.

    Maintenance

    ActivitySlowing
    ResponsivenessNo recent community issues

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