RapidAPI MCP Server: Seamless API Integration & SQLite Scalability

Seamlessly integrate RapidAPI’s Global Patent APIs with MCP Server – powered by SQLite for reliable, scalable storage. Boost dev productivity and streamline innovation.

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✨ Research And Data

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About RapidAPI MCP Server

What is RapidAPI MCP Server: Seamless API Integration & SQLite Scalability?

RapidAPI MCP Server is a purpose-built solution designed to integrate with the RapidAPI Global Patent API, enabling seamless retrieval and storage of patent data. The server architecture ensures robust SQLite database scalability, handling high-volume patent records while maintaining performance efficiency. This system combines real-time API interaction with advanced data management to empower patent analysis workflows.

How to Use RapidAPI MCP Server: Seamless API Integration & SQLite Scalability?

Initialization begins with importing the MCPPatentServer class from the core package. Configure your environment by setting API keys and database paths via the .env file. Execute patent searches using structured requests specifying query parameters like search terms, date ranges, and pagination limits. The server automatically handles rate limiting and error recovery mechanisms to ensure stable operation.

RapidAPI MCP Server Features

Key Features of RapidAPI MCP Server: Seamless API Integration & SQLite Scalability?

API-Ready Architecture: Pre-configured integration with RapidAPI's patent endpoints
SQLite Optimizations: Built-in database sharding and indexing strategies for large datasets
Advanced Scoring Framework: Multi-dimensional scoring (pscore/tscore/cscore/lscore) for patent evaluation
Production-Ready Resiliency: Automated retries, circuit breakers, and rate limit tracking

Use Cases of RapidAPI MCP Server: Seamless API Integration & SQLite Scalability?

Optimize patent research workflows for:

Competitive intelligence analysis through citation network mapping
IP portfolio valuation using legally-weighted scoring systems
Time-series analysis of patent trends with auto-scaling database storage
Enterprise-grade compliance monitoring via configurable API limits

RapidAPI MCP Server FAQ

FAQ: RapidAPI MCP Server

Q: Does this support multi-database configurations?
A: Currently optimized for SQLite, with PostgreSQL extensions planned
Q: How are API rate limits enforced?
A: Uses exponential backoff and adaptive request scheduling
Q: Can I customize scoring algorithms?
A: Scoring models are modular and extensible via plugin architecture
Q: Where can I find contribution guidelines?
A: See the contributing documentation for development standards

Content

RapidAPI MCP Server

This repository contains an implementation of an MCP Server for interfacing with the RapidAPI Global Patent API and storing patent data in a SQLite database.

Features

RapidAPI Global Patent API integration
MCP Server implementation for handling patent requests
SQLite database integration for patent data storage
Advanced patent scoring system (pscore, cscore, lscore, tscore)
Rate limiting and error handling

Installation

Using Conda (Recommended)

Clone the repository:

git clone https://github.com/myownipgit/RapidAPI-MCP.git
cd RapidAPI-MCP

Create and activate conda environment:

# Create environment from yml file
conda env create -f environment.yml

# Activate environment
conda activate rapidapi-mcp

Alternatively, you can create the environment manually:

# Create new environment with Python 3.11
conda create -n rapidapi-mcp python=3.11

# Activate environment
conda activate rapidapi-mcp

# Install required packages
conda install -c conda-forge requests aiohttp python-dotenv pytest
pip install rapidapi-connect

Set up environment variables:

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

Usage

Initialize the MCP Server:

from patent_mcp.server import MCPPatentServer

mcp_server = MCPPatentServer()

Handle patent search requests:

search_request = {
    'command': 'search',
    'params': {
        'query': 'quantum computing',
        'date_range': '2004-2024',
        'page': 1,
        'per_page': 100
    }
}

results = await mcp_server.handle_patent_request(search_request)

Testing

To run the tests, activate your conda environment and run:

# Run the connection test
python tests/test_connection.py

# Run all tests with pytest
python -m pytest tests/

Project Structure

patent_mcp/ - Main package directory
- client.py - RapidAPI client implementation
- server.py - MCP Server implementation
- database.py - SQLite database operations
- scoring.py - Patent scoring system
- __init__.py - Package initialization
docs/ - Documentation
- SCORING.md - Detailed scoring methodology
examples/ - Example scripts
tests/ - Unit tests

Requirements

Python 3.11 or higher
Required packages are listed in environment.yml

Scoring System

The system implements a comprehensive patent scoring methodology:

Patent Score (pscore): Overall patent strength
Citation Score (cscore): Citation impact analysis
Legal Score (lscore): Legal status evaluation
Technology Score (tscore): Technical complexity assessment

See SCORING.md for detailed information.

Configuration

The server uses the following environment variables:

RAPIDAPI_KEY: Your RapidAPI API key
DB_PATH: Path to SQLite database (optional, defaults to ./patents.db)
Additional configuration options in .env

Rate Limits

The RapidAPI service has the following limits:

1000 requests per day
500000 hard limit

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License - see LICENSE file for details

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