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

Download the DXT file
Open Claude Desktop
Go to Settings > Extensions
Click "Install from file" and select the .dxt file
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

Claude Desktop

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.

Cursor

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"
      }
    }
  }
}

Windsurf

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"
      }
    }
  }
}

VS Code

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"
        }
      }
    }
  }
}

Zed

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": {}
    }
  }
}

Cline

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": []
    }
  }
}

Using Alternative Package Managers

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"
      }
    }
  }
}

Windows Configuration

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

Get Your Team ID
```
get_current_user
```

Create a Project

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

Upload CSV Data

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

Check Processing Status

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

Generate Queries

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

Run a Query

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

Create Custom Query

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

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

"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
"Could not get default team ID"
- Check your API key permissions
- Ensure you have access to at least one team
File upload failures
- Verify the file path exists and is accessible
- Check file size limits (typically 100MB)
- Ensure the file is a valid CSV
Query execution timeouts
- Large datasets may take longer to process
- Consider breaking data into smaller chunks
- Check your Infactory plan limits
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

Fork the repository
Create a feature branch
Make your changes
Add tests for new functionality
Submit a pull request

License

MIT License - see LICENSE file for details.

Support

Documentation: https://docs.infactory.ai
Issues: GitHub Issues
Email: [email protected]

Changelog

v0.8.0

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

Name		Name	Last commit message	Last commit date
Latest commit History 34 Commits
.github/workflows		.github/workflows
examples		examples
src		src
test		test
.env.example		.env.example
.gitignore		.gitignore
Dockerfile		Dockerfile
README.md		README.md
infactory-mcp.dxt		infactory-mcp.dxt
manifest.json		manifest.json
mock-server.js		mock-server.js
package-lock.json		package-lock.json
package.json		package.json
tsconfig.json		tsconfig.json
tsconfig.test.json		tsconfig.test.json
vitest.config.ts		vitest.config.ts
vitest.e2e.config.ts		vitest.e2e.config.ts

infactory-io/infactory-mcp

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