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Infactory MCP Desktop Extension (DXT)

A Desktop Extension (DXT) that provides seamless access to Infactory's data analysis and API generation capabilities through Claude Desktop and other MCP clients.

Overview

Infactory transforms articles, data, and archives into AI-ready formats that can be safely queried, cited and licensed. This DXT extension provides a complete workflow from data upload to API deployment.

Features

  • Data Management: Upload CSV files and manage datasources
  • Query Generation: Auto-generate queries or create custom ones from natural language
  • API Deployment: Publish query programs as live API endpoints
  • Chat Integration: Explore data through conversational interfaces
  • Project Management: Create and manage projects and teams

Installation

For Claude Desktop Users

  1. Download the DXT file
  2. Open Claude Desktop
  3. Go to Settings > Extensions
  4. Click "Install from file" and select the .dxt file
  5. Configure your Infactory API key in the extension settings (see Configuration section below)

For Developers

# Clone the repository
git clone https://github.com/infactory/infactory-mcp.git
cd infactory-mcp

# Install dependencies
npm install

# Build the extension
npm run build

# Package as DXT
npm run dxt:pack

Installing via NPM

The package is also available on npm as @infactory/infactory-mcp:

# Install globally
npm install -g @infactory/infactory-mcp

# Or use with npx
npx @infactory/infactory-mcp

Configuration

The extension requires configuration through the DXT user interface. After installation, you'll need to configure the following settings:

Required Settings

  • Infactory API Key: Your Infactory API key (get this from your Infactory dashboard)
    • This is a sensitive field that will be stored securely
    • Required for all API operations

Optional Settings

  • Infactory API Base URL: API base URL (defaults to https://api.infactory.ai)
    • Only change this if you're using a custom Infactory instance
    • Optional field with a sensible default

Connection Samples

Add this to your Claude Desktop claude_desktop_config.json file:

{
  "mcpServers": {
    "infactory-mcp": {
      "command": "npx",
      "args": ["-y", "@infactory/infactory-mcp"],
      "env": {
        "NF_API_KEY": "nf--YOUR_API_KEY_HERE",
        "NF_BASE_URL": "https://api.infactory.ai"
      }
    }
  }
}

Note: Replace nf--YOUR_API_KEY_HERE with your actual Infactory API key.

Add this to your Cursor MCP config file (usually at ~/.cursor/mcp.json):

{
  "mcpServers": {
    "infactory-mcp": {
      "command": "npx",
      "args": ["-y", "@infactory/infactory-mcp"],
      "env": {
        "NF_API_KEY": "nf--YOUR_API_KEY_HERE",
        "NF_BASE_URL": "https://api.infactory.ai"
      }
    }
  }
}

Add this to your Windsurf MCP config file:

{
  "mcpServers": {
    "infactory-mcp": {
      "command": "npx",
      "args": ["-y", "@infactory/infactory-mcp"],
      "env": {
        "NF_API_KEY": "nf--YOUR_API_KEY_HERE",
        "NF_BASE_URL": "https://api.infactory.ai"
      }
    }
  }
}

Add this to your VS Code MCP config file:

{
  "mcp": {
    "servers": {
      "infactory-mcp": {
        "type": "stdio",
        "command": "npx",
        "args": ["-y", "@infactory/infactory-mcp"],
        "env": {
          "NF_API_KEY": "nf--YOUR_API_KEY_HERE",
          "NF_BASE_URL": "https://api.infactory.ai"
        }
      }
    }
  }
}

Add this to your Zed settings.json:

{
  "context_servers": {
    "infactory-mcp": {
      "command": {
        "path": "npx",
        "args": ["-y", "@infactory/infactory-mcp"],
        "env": {
          "NF_API_KEY": "nf--YOUR_API_KEY_HERE",
          "NF_BASE_URL": "https://api.infactory.ai"
        }
      },
      "settings": {}
    }
  }
}

Add this to your Cline MCP settings:

{
  "mcpServers": {
    "infactory-mcp": {
      "command": "npx",
      "args": ["-y", "@infactory/infactory-mcp"],
      "env": {
        "NF_API_KEY": "nf--YOUR_API_KEY_HERE",
        "NF_BASE_URL": "https://api.infactory.ai"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

With Bun

{
  "mcpServers": {
    "infactory-mcp": {
      "command": "bunx",
      "args": ["-y", "@infactory/infactory-mcp"],
      "env": {
        "NF_API_KEY": "nf--YOUR_API_KEY_HERE",
        "NF_BASE_URL": "https://api.infactory.ai"
      }
    }
  }
}

With Deno

{
  "mcpServers": {
    "infactory-mcp": {
      "command": "deno",
      "args": ["run", "--allow-env", "--allow-net", "npm:@infactory/infactory-mcp"],
      "env": {
        "NF_API_KEY": "nf--YOUR_API_KEY_HERE",
        "NF_BASE_URL": "https://api.infactory.ai"
      }
    }
  }
}

For Windows users, the configuration is slightly different:

{
  "mcpServers": {
    "infactory-mcp": {
      "command": "cmd",
      "args": ["/c", "npx", "-y", "@infactory/infactory-mcp"],
      "env": {
        "NF_API_KEY": "nf--YOUR_API_KEY_HERE",
        "NF_BASE_URL": "https://api.infactory.ai"
      }
    }
  }
}

Usage

Quick Start Workflow

  1. Get Your Team ID

    get_current_user

  2. Create a Project

    create_project {"name": "My Analysis Project", "teamId": "team-..."}

  3. Upload CSV Data

    upload_csv {"projectId": "proj-...", "filePath": "/path/to/data.csv", "datasourceName": "My Data"}

  4. Check Processing Status

    get_datasource_status {"datasourceId": "ds-..."}

  5. Generate Queries

    autogenerate_queries {"projectId": "proj-...", "count": 3}

  6. Run a Query

    run_query_program {"projectId": "proj-...", "queryProgramId": "qp-..."}

  7. Create Custom Query

    create_query_from_nl {"projectId": "proj-...", "question": "What is the average value by category?"}

  8. Publish as API

    publish_query_program {"queryProgramId": "qp-..."}

Available Tools

User & Project Management

  • get_current_user - Get user profile and team information
  • create_project - Create a new project
  • list_projects - List all projects in a team
  • delete_project - Delete a project

Data Management

  • upload_csv - Upload a CSV file to create a datasource
  • get_datasource_status - Check datasource processing status
  • delete_datasource - Delete a datasource

Query Building

  • autogenerate_queries - Generate starter queries based on data
  • create_query_from_nl - Create query from natural language
  • list_query_programs - List all query programs in a project

Query Execution

  • run_query_program - Execute a query program
  • publish_query_program - Publish query as live API

API Management

  • list_apis - List deployed APIs
  • list_api_endpoints - List API endpoints
  • call_live_api - Call a live API endpoint

Chat & Explore

  • create_conversation - Start a chat session
  • send_chat_message - Send a message in chat
  • get_conversation_graph - Get conversation interaction graph

Development

Prerequisites

  • Node.js 18+
  • npm or yarn
  • TypeScript

Setup

# Install dependencies
npm install

# Build the project
npm run build

# Run in development mode
npm run dev

# Run tests
npm test

# Validate DXT manifest
npm run dxt:validate

Testing with MCP Inspector

# Run the MCP inspector to test tools
npm run inspector

# Or use npx directly
npx @modelcontextprotocol/inspector npx @infactory/infactory-mcp

Building for Distribution

# Build and package as DXT
npm run dxt:pack

This creates a .dxt file that can be distributed and installed in Claude Desktop.

Error Handling

The extension includes comprehensive error handling:

  • Timeout Management: All API calls have appropriate timeouts
  • Configuration Validation: Ensures required settings are present
  • Graceful Degradation: Handles network and API errors gracefully
  • Detailed Logging: Provides clear error messages for debugging

Security

  • API keys are stored securely using the host's secure storage
  • Sensitive configuration fields are marked appropriately
  • All API calls use HTTPS with proper authentication

Troubleshooting

Common Issues

  1. "NF_API_KEY not set"

    • Ensure you've configured the "Infactory API Key" in the extension settings
    • Verify the key is valid in your Infactory dashboard
    • Check that the configuration was saved properly

  2. "Could not get default team ID"

    • Check your API key permissions
    • Ensure you have access to at least one team

  3. File upload failures

    • Verify the file path exists and is accessible
    • Check file size limits (typically 100MB)
    • Ensure the file is a valid CSV

  4. Query execution timeouts

    • Large datasets may take longer to process
    • Consider breaking data into smaller chunks
    • Check your Infactory plan limits

  5. Module resolution issues

    • Try using bunx instead of npx if you encounter module errors
    • Ensure Node.js v18 or higher is installed
    • Use @infactory/infactory-mcp@latest to get the latest version

Debug Mode

Enable debug logging by setting the DEBUG environment variable:

DEBUG=* npm run dev

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add tests for new functionality
  5. Submit a pull request

License

MIT License - see LICENSE file for details.

Support

Changelog

v0.8.0

  • Initial DXT release
  • Complete MCP server implementation
  • All core Infactory functionality
  • Comprehensive error handling and timeouts
  • DXT packaging and validation

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