jobtread

JobTread MCP Server provides an interface to query JobTread construction management data through the Model Context Protocol (MCP). It enables you to search for construction projects, customers, and documents, fetch detailed project information, and keep data synchronized in real time with the JobTread API. This server is designed for use with ChatGPT Connectors and other AI research workflows to enable deeper, context-aware construction management insights and tasks.

To use the server, deploy it to your preferred hosting environment and ensure the required environment variables are configured. Once running, connect your MCP client (or ChatGPT Connector) to the server name/jobtread. The server will expose endpoints for search and fetch operations, returning structured model-context data that can be used to drive AI-assisted project planning, reporting, and document management workflows.

Prerequisites:

• Node.js 14+ and npm installed on your machine
• Access to a JobTread API key and organization ID

Installation steps:

1. Clone the repository containing the MCP server: git clone https://github.com/carlosvino-jobtread-mcp-server.git cd carlosvino-jobtread-mcp-server

2. Install dependencies: npm install

3. Configure environment variables (either via a .env file or your hosting platform's config): JOBTREAD_API_KEY=your_jobtread_api_key JOBTREAD_ORG_ID=your_organization_id

4. Start the MCP server (adjust the path to your actual entry script if different): node path/to/server.js

5. Verify the server is running by checking the logs or hitting the MCP endpoint configured for the jobtread server.

Tips and common issues:

• Ensure the JobTread API key has the necessary permissions to access projects, customers, and documents.
• If your hosting environment requires a different startup command, update the mcp_config accordingly (e.g., using uvx or npx if packaged that way).
• For local development, consider creating a .env file with JOBTREAD_API_KEY and JOBTREAD_ORG_ID and load it with a tool like dotenv if your server supports it.
• If responses are missing fields, enable verbose logging or inspect the MCP schema to confirm the expected properties for projects, customers, and documents.
• When deploying to Railway or similar platforms, ensure the environment variables are set in the platform’s configuration panel for the service.
• If you plan to expose the server publicly, implement appropriate access controls and rate limiting to protect your API keys.