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Quick Chart MCP Server

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A Model Context Protocol (MCP) server that provides chart tools, allowing it to interact with the quick chart through a standardized interface. This implementation is based on the chart definition and enables users can open quick chart pages seamlessly.

Overview

This MCP server tools:

  • Interact with Quick Chart

The server implements the Model Context Protocol specification to standardize chart interactions for AI agents.

Prerequisites

  • Node.js (v16 or higher)

  • pnpm (recommended), npm, or yarn

Installation

Installing via Smithery

To install quick-chart-mcp for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @datafe/quick-chart-mcp --client claude

Option 1: Install from npm (recommend for clients like Cursor/Cline)

# Install globally npm install -g quick-chart-mcp # Or install locally in your project npm install quick-chart-mcp

Option 2: Build from Source (for developers)

  1. Clone this repository:

git clone https://github.com/datafe/quick-chart-mcp cd quick-chart-mcp
  1. Install dependencies (pnpm is recommended, npm is supported):

pnpm install
  1. Build the project:

pnpm run build
  1. Development the project (by @modelcontextprotocol/inspector):

pnpm run dev

open http://localhost:5173

Configuration

MCP Configs

{ "mcpServers": { "quick-chart-mcp": { "autoApprove": [], "disabled": false, "timeout": 300, "command": "npx", "args": [ "quick-chart-mcp@1.0.13" ], "transportType": "stdio" } } }

Environment Setup

Create a .env file with your credentials:

# Quick Chart Configuration NODE_ENV=optional_development_or_product QUICK_CHART_DRAW_URL=optional_quick_chart_draw_url NEED_INSTALL_QUICK_CHART=optional_true_or_false

Project Structure

quick-chart-mcp/ ├── src/ │ ├── index.ts # Main entry point ├── package.json └── tsconfig.json

Available Tools

The MCP server provides the following Quick Chart tools:

  • GetChartImgLink - Retrieve chart image link by parameters.

  • InstallQuickChart - Install quick chart service locally.

Security Considerations

  • Use environment variables for sensitive information

  • Regularly monitor and audit AI agent activities

Troubleshooting

If you encounter issues:

  1. Verify the build was successful

Dependencies

image APIs.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

  1. Fork the repository

  2. Create your feature branch (git checkout -b feature/amazing-feature)

  3. Commit your changes (git commit -m 'Add some amazing feature')

  4. Push to the branch (git push origin feature/amazing-feature)

  5. Open a Pull Request

License

This project is licensed under the MIT License.

Deploy Server
A
security – no known vulnerabilities
A
license - permissive license
A
quality - confirmed to work

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/datafe/quick-chart-mcp'

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