Overview
What is Pulse Backend MCP Server?
A Model Context Protocol (MCP) server that provides BigQuery access and specialized data tools for developers within the company to increase productivity. It implements the MCP protocol to enable LLM-powered applications to access company data and execute specialized data functions in a controlled manner.
How to use Pulse Backend MCP Server?
Clone the repository, create a Python 3.13+ virtual environment, install dependencies, and configure Google Cloud credentials (via GOOGLE_APPLICATION_CREDENTIALS environment variable) and a .env file with GOOGLE_PROJECT_ID and CLICKUP_API_KEY. Start the server with mcp dev src/server.py on the default MCP port (typically 8080). Connect MCP-compatible clients (e.g., Claude Desktop) to discover and use the provided tools.
Key features of Pulse Backend MCP Server
- BigQuery Integration: Execute SQL queries against company BigQuery datasets
- Client Data Access: Retrieve client details and datasets from the data warehouse
- List tables in any BigQuery dataset with metadata
- Retrieve ClickUp task details with subtasks and comments
- Extensible architecture: add new tools by decorating functions in
server.py
Use cases of Pulse Backend MCP Server
- A developer queries BigQuery for real-time sales data to inform product decisions
- A support agent retrieves client details and associated datasets quickly
- A data analyst lists and explores tables in a BigQuery dataset
- A project manager fetches ClickUp task details and comments without leaving the AI chat
- A team member extends the server with custom tools for new data sources
FAQ from Pulse Backend MCP Server
What is the Model Context Protocol (MCP)?
MCP is an open protocol that standardizes how applications provide context to LLMs, similar to how USB-C standardizes connections to peripherals. It enables AI models to connect to different data sources and tools through a client-server architecture.
