MCP.so
Sign In

Pulse Backend MCP Server

@ashyam-saras

Basic information

Category

Other

Transports

stdio

Author

ashyam-saras

About Pulse Backend MCP Server

MCP server code for Saras

Pulse Backend MCP Server config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

Pulse Backend MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

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

Frequently asked questions

1

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.

Comments

More Other MCP servers