Convertagent

ConvertAgent is a self-hosted, open-source file conversion toolkit designed for AI agents. Your files never leave your infrastructure — no cloud uploads, no API keys, no per-conversion fees, no usage limits. Just install, run, and convert. CLI for local agents, REST API for remote access, and MCP for the agent ecosystem.

Self-hosted. Open source. Zero cost per conversion. Your agent converts files locally — no cloud, no limits, no vendor lock-in.

✨ Features

• 🖥️ CLI-first — convertagent convert file.pdf --to docx — the native interface for agents
• 🌐 REST API — POST /v1/convert for remote agents and web services
• 🔌 MCP Server — Discoverable by any MCP-compatible AI client (Claude, ChatGPT, Cursor, etc.)
• ⚡ One dispatcher — All three interfaces share the same conversion engine
• 📦 20 conversion pairs across documents, images, audio/video, and text
• 🔧 Open-source engines — FFmpeg, LibreOffice, ImageMagick, Pandoc under the hood
• 🚀 Self-hosted — Your files never leave your infrastructure

📋 Supported Conversions

🚀 Quick Start

Prerequisites

# Install conversion engines (Ubuntu/Debian)
sudo apt-get update && sudo apt-get install -y ffmpeg libreoffice imagemagick pandoc

Install & Run

git clone https://github.com/vid-factory/convertagent.git
cd convertagent
npm install
npm run build

CLI Usage

# Convert a PDF to Word
convertagent convert report.pdf --to docx

# Convert with custom output path
convertagent convert photo.png --to webp --output ./compressed.webp

# Extract audio from video
convertagent convert video.mp4 --to mp3

# List all supported formats
convertagent formats

# Check engine health
convertagent health

Start the API Server

# Start on default port 3001
node dist/api/server.js

# Or with custom port
PORT=8080 node dist/api/server.js

📡 API Reference

POST /v1/convert

Convert a file from one format to another.

Request:

{
  "action": "pdf-to-docx",
  "source": "/path/to/file.pdf",
  "options": {}
}

With URL source:

{
  "action": "html-to-pdf",
  "source_url": "https://example.com/page.html",
  "options": {}
}

With base64 source:

{
  "action": "jpg-to-png",
  "source_base64": "data:image/jpeg;base64,/9j/4AAQ...",
  "options": {}
}

Response:

{
  "success": true,
  "job_id": "a1b2c3d4",
  "artifact": {
    "path": "/output/a1b2c3d4.docx",
    "url": "/v1/artifacts/a1b2c3d4",
    "format": "docx",
    "size": 45231,
    "duration_ms": 1200
  }
}

GET /v1/formats

List all supported conversion pairs.

GET /health

Check engine availability.

{
  "ok": true,
  "service": "convertagent",
  "engines": {
    "ffmpeg": true,
    "libreoffice": true,
    "imagemagick": true,
    "pandoc": true
  }
}

🔌 MCP Server

ConvertAgent exposes an MCP server for integration with any MCP-compatible AI client.

Available Tools

Connect via MCP

{
  "mcpServers": {
    "convertagent": {
      "url": "http://localhost:3001/mcp"
    }
  }
}

Example: Claude Desktop

Add to your Claude Desktop MCP config:

{
  "mcpServers": {
    "convertagent": {
      "command": "node",
      "args": ["/path/to/convertagent/dist/mcp/server.js"]
    }
  }
}

🏗️ Architecture

┌─────────────────────────────────────────────────────┐
│                    ConvertAgent                       │
│                                                       │
│  ┌─────────┐  ┌─────────┐  ┌─────────┐              │
│  │   CLI   │  │   API   │  │   MCP   │  ← Interfaces│
│  └────┬────┘  └────┬────┘  └────┬────┘              │
│       │            │            │                     │
│       └────────────┼────────────┘                     │
│                    │                                  │
│           ┌────────▼────────┐                         │
│           │   Dispatcher    │  ← Shared routing core  │
│           └────────┬────────┘                         │
│                    │                                  │
│    ┌───────┬───────┼───────┬────────┐                │
│    │       │       │       │        │                │
│  ┌─▼──┐ ┌─▼──┐ ┌──▼──┐ ┌─▼────┐   │                │
│  │ FF │ │ LO │ │ IM  │ │ Pan  │   │  ← Engines     │
│  │mpeg│ │    │ │     │ │ doc  │   │                 │
│  └────┘ └────┘ └─────┘ └──────┘   │                │
│                                     │                │
│  FF = FFmpeg    LO = LibreOffice    │                │
│  IM = ImageMagick  Pan = Pandoc     │                │
└─────────────────────────────────────────────────────┘

🐳 Docker (Coming Soon)

docker run -p 3001:3001 vid-factory/convertagent

🛠️ Development

# Clone
git clone https://github.com/vid-factory/convertagent.git
cd convertagent

# Install dependencies
npm install

# Build
npm run build

# Run tests
npm test

# Run the full 20-pair conversion test matrix
node scripts/run-tea-20.mjs

Project Structure

convertagent/
├── src/
│   ├── cli/              # CLI commands (convert, formats, health)
│   ├── api/              # REST API server (Fastify)
│   ├── mcp/              # MCP server (Streamable HTTP)
│   ├── core/             # Shared dispatcher + format registry
│   ├── engines/          # Engine adapters
│   │   ├── ffmpeg.ts     # Audio/video conversions
│   │   ├── libreoffice.ts# Document conversions
│   │   ├── imagemagick.ts# Image conversions
│   │   ├── pandoc.ts     # Text/markup conversions
│   │   └── shell.ts      # Shared shell runner with timeouts
│   └── tests/            # Unit + integration tests
├── scripts/              # TEA matrix runner, utilities
├── test-assets/          # Real input files for testing
├── test-artifacts/       # TEA results + parity evidence
├── deploy/               # systemd service file
├── package.json
├── tsconfig.json
└── README.md

📊 Test Results

ConvertAgent ships with a full real-file test matrix — no mocks.

20/20 passing — verified across CLI, API, and MCP interfaces with binary parity checks.

🗺️ Roadmap

• CLI interface with 20 conversion pairs
• REST API (/v1/convert, /v1/formats, /health)
• MCP server with tool discovery + execution
• Real-file TEA test matrix (20/20)
• Cross-interface parity verification (CLI = API = MCP)
• systemd deployment for persistence
• URL source intake (fetch remote files for conversion)
• Docker image for one-command deployment
• OpenClaw skill package (publish to ClawHub)
• Claw Mart marketplace listing
• Pipeline endpoint (chain multiple conversions)
• npm global install (npm install -g convertagent)
• Usage tracking + rate limiting
• Additional format pairs (50+)

🤝 Contributing

Contributions are welcome! Please follow these guidelines:

1. Fork the repository
2. Create a feature branch (git checkout -b feat/new-format-pair)
3. Write tests for new conversions (use real files, not mocks)
4. Run the full TEA matrix (node scripts/run-tea-20.mjs)
5. Commit with conventional commits (feat:, fix:, docs:, test:)
6. Open a Pull Request

Adding a New Conversion Pair

1. Add the format pair to src/core/formats.ts
2. Implement or extend the appropriate engine adapter in src/engines/
3. Add a real test input file to test-assets/input/
4. Add the pair to the TEA matrix in scripts/run-tea-20.mjs
5. Run tests and verify output

📄 License

MIT License — see LICENSE for details.

🙏 Acknowledgments

• FFmpeg — Audio/video processing
• LibreOffice — Document conversions
• ImageMagick — Image processing
• Pandoc — Universal document converter
• Model Context Protocol — The standard for AI tool integration