nitish1888/idea-hub-mcp-server

Idea Hub MCP Server

A Model Context Protocol (MCP) server for the Idea Hub AI-powered innovation platform. This server provides tools for AI agents to interact with the idea management system, including semantic search, duplicate detection, contributor matching, and AI-powered analysis.

Features

Core Functionality

• Semantic Search: AI-powered search using vector embeddings
• Duplicate Detection: Identify similar ideas to prevent redundancy
• Contributor Matching: Match ideas with skilled contributors
• AI Analysis: Generate summaries, assess feasibility, and suggest improvements

MCP Tools Available

Idea Management Tools

• search_ideas - Search for ideas using semantic, keyword, or hybrid search
• get_idea_details - Get detailed information about a specific idea
• detect_duplicates - Detect duplicate or similar ideas
• analyze_idea_trends - Analyze trends in submitted ideas

Contributor Tools

• search_contributors - Search for contributors by skills or availability
• match_contributors_to_idea - Find contributors that match an idea's requirements

AI Analysis Tools

• generate_idea_summary - Generate AI summary of an idea
• assess_idea_feasibility - Assess technical and business feasibility
• suggest_improvements - Suggest improvements for an idea

Architecture

Technology Stack

• MCP Protocol: Model Context Protocol for AI agent interactions
• Database: PostgreSQL with pgvector extension for vector operations
• AI Models:
  • Google Gemini for reasoning and text generation
  • HuggingFace Sentence Transformers for embeddings
• Vector Operations: Sentence Transformers with PostgreSQL pgvector
• Language: Python 3.12+ with async/await support

Key Components

• Server Core: Main MCP server implementation (src/server.py)
• Tool Modules: Specialized tools for different domains (src/tools/)
• Database Layer: Async PostgreSQL operations (src/utils/database.py)
• Configuration: Environment-based configuration (src/utils/config.py)

Installation

Prerequisites

• Python 3.12+
• PostgreSQL with pgvector extension
• Google API key for Gemini AI
• HuggingFace account (optional, for some models)

Setup

1. Clone the repository:

   git clone git@gitlab.cee.company.com:nitsingh/idea_hub_mcp_server.git
   cd idea-hub-mcp-server
   

2. Install dependencies:

   pip install -e .
   

3. Set up environment variables:

   cp env.example .env
   # Edit .env with your configuration
   

4. Set up the database:

   CREATE EXTENSION IF NOT EXISTS vector;
   

Configuration

Environment Variables

Create a .env file with the following variables:

# Database Configuration
DB_HOST=localhost
DB_PORT=5432
DB_NAME=idea_hub
DB_USER=postgres
DB_PASSWORD=your_password

# AI Configuration
GOOGLE_API_KEY=your_google_api_key
HUGGINGFACE_TOKEN=your_hf_token  # Optional
EMBEDDING_MODEL=all-MiniLM-L6-v2
LLM_MODEL=gemini-pro

# Server Configuration
SERVER_HOST=localhost
SERVER_PORT=8000
LOG_LEVEL=INFO
DEBUG=false

# Vector Configuration
VECTOR_DIMENSION=384
SIMILARITY_THRESHOLD=0.7
MAX_VECTOR_RESULTS=10

Usage

Running the Server

# Run directly
python -m src.main

# Or using the installed script
idea-hub-mcp-server

Connecting to the Server

The server implements the MCP protocol and can be used by any MCP-compatible AI agent or client.

Example MCP client connection:

{
  "method": "tools/list",
  "params": {}
}

Tool Usage Examples

Search Ideas

{
  "method": "tools/call",
  "params": {
    "name": "search_ideas",
    "arguments": {
      "query": "machine learning automation",
      "search_type": "semantic",
      "limit": 5
    }
  }
}

Detect Duplicates

{
  "method": "tools/call",
  "params": {
    "name": "detect_duplicates",
    "arguments": {
      "title": "AI-powered chatbot for customer service",
      "description": "Implement an intelligent chatbot using natural language processing...",
      "threshold": 0.8
    }
  }
}

Match Contributors

{
  "method": "tools/call",
  "params": {
    "name": "match_contributors_to_idea",
    "arguments": {
      "idea_id": 123,
      "required_skills": ["Python", "Machine Learning", "API Development"],
      "max_contributors": 3
    }
  }
}

Development

Project Structure

idea-hub-mcp-server/
├── src/
│   ├── main.py              # Entry point
│   ├── server.py            # Main MCP server
│   ├── tools/               # Tool implementations
│   │   ├── idea_tools.py    # Idea management
│   │   ├── vector_tools.py  # Vector operations
│   │   ├── contributor_tools.py  # Contributor matching
│   │   └── ai_tools.py      # AI analysis
│   └── utils/               # Utilities
│       ├── config.py        # Configuration
│       └── database.py      # Database operations
├── tests/                   # Test suite
├── pyproject.toml          # Project configuration
├── env.example             # Environment template
└── README.md               # This file

Running Tests

# Install dev dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Run with coverage
pytest --cov=src

Code Quality

# Format code
ruff format

# Lint code
ruff check

# Type checking
mypy src

Integration with Idea Hub

This MCP server is designed to work alongside the main Idea Hub application, providing AI agent capabilities to:

1. Enhance Idea Submission: Detect duplicates and suggest improvements during submission
2. Smart Search: Enable semantic search across all ideas
3. Contributor Matching: Automatically suggest contributors for new ideas
4. AI Analysis: Provide automated feasibility assessments and summaries

Team

• Designed By: Nitish Singh (https://www.linkedin.com/in/nitish-singh-11aa0239/)
• Key Contributors:Rishika Kumar (https://www.linkedin.com/in/riishika/) and Shubham (https://www.linkedin.com/in/shubham-chilhate-362863213/)

License

This project is part of Company's innovation initiatives and follows internal licensing guidelines.

Support

For questions or issues, please contact the development team or create an issue in the project repository.