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Foxit PDF API MCP Server

Provides MCP tools to manage, convert, secure, and analyze PDFs via Foxit Cloud PDF API.

Installation
Add the following to your MCP client configuration file.

Configuration

View docs
{
  "mcpServers": {
    "foxitsoftware-foxit-pdf-api-mcp-server": {
      "command": "uv",
      "args": [
        "--directory",
        "/absolute/path/to/foxit-pdf-api-mcp-server",
        "run",
        "foxit-pdf-api-mcp-server"
      ],
      "env": {
        "FOXIT_CLOUD_API_HOST": "https://na1.fusion.foxit.com/pdf-services",
        "FOXIT_CLOUD_API_CLIENT_ID": "your_client_id",
        "FOXIT_CLOUD_API_CLIENT_SECRET": "your_client_secret"
      }
    }
  }
}

You can use this MCP server to access Foxit Cloud PDF API operations through compatible MCP clients. It exposes a broad set of PDF capabilities—creating, converting, manipulating, securing, and analyzing PDFs—so you can automate document workflows with AI agents or other MCP-enabled tools.

How to use

Connect your MCP client to the Foxit PDF API MCP Server using the provided stdio configuration. Your client will invoke tools such as uploading documents, downloading results, and performing common PDF operations. The server handles authentication with your Foxit Cloud credentials and passes requests to the Foxit Cloud PDF services, returning results that your agent can use in subsequent steps.

How to install

Prerequisites you need before installing the MCP server:

- Python 3.11 or higher

- uv package manager (recommended) or pip

Install with uv (Recommended)

# Clone or download the repository
cd foxit-pdf-api-mcp-server

# Install with uv
uv pip install -e .

Install with pip

pip install -e .

Configuration

Set up environment variables to provide access to Foxit Cloud PDF services. Create a .env file or export these values in your shell. Use the North America host as an example when configuring your region.

Environment variables

# API Base URL (choose your region)
# North America:
FOXIT_CLOUD_API_HOST=https://na1.fusion.foxit.com/pdf-services

# API Credentials
FOXIT_CLOUD_API_CLIENT_ID=your_client_id
FOXIT_CLOUD_API_CLIENT_SECRET=your_client_secret

Integration

Example integration snippet for a code editor to run the server via the recommended approach. This configuration works with MCP clients that expect a standard stdio server interface.

Usage examples

Upload and download workflows are demonstrated in practical scenarios. For example, you can instruct your agent to upload a document and later download a processed file. These actions are performed by the server using the upload_document and download_document tools.

Development

If you plan to contribute or run development tasks, install development dependencies and start the server in HTTP or stdio mode as shown. Use the provided commands to run the server locally for testing.

Troubleshooting

If you encounter import or authentication issues, ensure you have installed the package with the same command you used for runtime, and verify your Foxit Cloud credentials are correct by inspecting their environment variables.

Notes

The server exposes a broad set of PDF operations, ranging from document lifecycle management to security and metadata analysis. It is designed to be used by AI agents and MCP-compatible tools that can interact with the Foxit Cloud PDF API.

Security considerations

Keep your API client credentials secure. Do not commit them to source control or expose them in public environments. Use secret management where possible and rotate credentials periodically.

Supported environments

The server is configured for Python environments and can be run via the uv package manager or pip. Ensure the host environment has network access to the Foxit Cloud PDF services.

Notes on environment variables

All shown environment variables are required for successful authentication and region configuration. Ensure values are provided exactly as shown and kept secure.

Available tools

upload_document

Upload a document to the server so it can be referenced by subsequent operations.

download_document

Download a previously uploaded document or its processed output to a local path.