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Bloomy MCP

A Model Context Protocol (MCP) server for interacting with Bloom Growth's GraphQL API.

Overview

Bloomy MCP is a server that connects to Bloom Growth's GraphQL API and exposes it through the Model Context Protocol, enabling AI assistants to perform operations against the Bloom Growth platform.

Related MCP server: Confluence MCP

Features

  • Query Bloom Growth GraphQL API through MCP

  • Retrieve query and mutation details

  • Execute GraphQL queries and mutations via MCP tools

  • Get authenticated user information

  • Automatic schema introspection

Installation

Prerequisites

  • Python 3.12 or higher

  • Access to Bloom Growth API

  • uv (recommended) or pip for package management

Package Management

This project recommends using uv, a fast Python package installer and resolver that serves as a drop-in replacement for pip/pip-tools. It's significantly faster than traditional package managers.

Installing uv

curl -sSf https://astral.sh/uv/install.sh | sh

For other installation methods, see the uv documentation.

Setup

  1. Clone this repository

  2. Set up a Python virtual environment:

    python -m venv .venv source .venv/bin/activate # On Windows: .venv\Scripts\activate
  3. Install the package in development mode:

    Using pip:

    pip install -e .

    Using uv (recommended):

    uv pip install -e .

    For development dependencies:

    uv pip install -e ".[dev]"

Environment Variables

Create a .env file with the following variables:

BLOOM_API_URL=<Your Bloom API URL> BLOOM_API_TOKEN=<Your Bloom API Token>

Usage

Cursor Integration

To use this MCP server with Cursor (AI-powered IDE):

  1. Go to Cursor > Cursor Settings > MCP

  2. Click on "Add new MCP server"

  3. Configure the server with the following details:

    • Name: "Bloom Growth" (or "BG" or any name you prefer)

    • Type: Command

    • Command: uv run --project /path/to/your/repo/ --env-file /path/to/your/repo/.env bloomy-server

    Important: Replace /path/to/your/repo/ with the actual path to your bloomy-mcp repository (e.g., /Users/username/workspace/bloomy-mcp/).

Running the Server

Start the Bloomy MCP server:

bloomy-server

Development Mode Inspection

For development and debugging purposes, you can use the MCP inspector tool:

npx @modelcontextprotocol/inspector bloomy-server

This allows you to inspect the MCP server's behavior and responses during development.

Recommended Tools

For optimal development workflow:

  • direnv: Use for managing environment variables and automatically loading them when entering the project directory

  • uv: Use for fast and reliable package management

Setting up direnv:

  1. Install direnv (e.g., brew install direnv on macOS)

  2. Create a .envrc file in your project root:

    export BLOOM_API_URL=your_api_url export BLOOM_API_TOKEN=your_api_token
  3. Run direnv allow to authorize the environment variables

This combination of tools (direnv + uv) provides an efficient environment for both secrets management and package management.

Available MCP Tools

The following MCP tools are available for AI assistants:

  • get_query_details - Get detailed information about specific GraphQL queries

  • get_mutation_details - Get detailed information about specific GraphQL mutations

  • execute_query - Execute a GraphQL query or mutation with variables

  • get_authenticated_user_id - Get the ID of the currently authenticated user

Available MCP Resources

  • bloom://queries - Get a list of all available queries

  • bloom://mutations - Get a list of all available mutations

Development

Project Structure

src/ └── bloomy_mcp/ ├── __init__.py # Package initialization ├── client.py # GraphQL client implementation ├── formatters.py # Data formatting utilities ├── introspection.py # GraphQL schema introspection ├── operations.py # GraphQL operation utilities └── server.py # MCP server implementation

Dependencies

  • mcp[cli] - Model Context Protocol server

  • gql - GraphQL client library

  • httpx - HTTP client

  • pyyaml - YAML processing

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