mpc-sintific-search-by-ai-for-ai

mpc-sintific-search-by-ai-for-ai

0
research_and_data

This project is a Model Control Protocol implementation designed to provide academic search capabilities for Cursor, integrating multiple search engines like Google Scholar and PubMed. It features Tor proxy usage to bypass rate limits, enhancing research efficiency via scientific search tools.

Scientific Search MCP for Cursor

[!WARNING] Vibecoded by AI.

This is a Model Control Protocol (MCP) implementation for Cursor that provides scientific search capabilities through various academic search engines.

Features

  • Integration with Cursor using the MCP protocol
  • Scientific search across multiple engines:
    • DuckDuckGo (general web search)
    • Google Scholar (academic papers search)
    • PubMed (biomedical literature search)
    • arXiv (physics, mathematics, computer science, etc.)
    • Semantic Scholar (AI-powered research paper search via Tor proxy)

Installation

  1. Clone this repository:
git clone https://github.com/yourusername/cursor-scientific-search.git
cd cursor-scientific-search
  1. Install the required dependencies:
pip install -r requirements.txt

For specific search engines, you may need to install additional dependencies:

# For arXiv search
pip install arxiv

# For Google Scholar
pip install scholarly

# For PubMed
pip install pymed

# For Semantic Scholar (requires Tor)
pip install requests[socks]

Tor Setup for Semantic Scholar

The Semantic Scholar search uses Tor to bypass rate limits and IP blocks. To use this feature:

  1. Install Tor:

    • Linux: sudo apt install tor (Debian/Ubuntu) or sudo pacman -S tor (Arch)
    • macOS: brew install tor
    • Windows: Download and install the Tor Browser which includes the Tor service

  2. Start the Tor service:

    • Linux: sudo systemctl start tor or sudo service tor start
    • macOS: brew services start tor
    • Windows: The Tor Browser includes the service, or you can use Tor Expert Bundle

  3. Verify Tor is running on port 9050 (default):

    nc -z localhost 9050 && echo "Tor is running"

  4. The scientific search MCP will automatically route Semantic Scholar requests through Tor.

Usage

  1. Start the MCP server:
python scientific_search_mcp.py

  1. In Cursor, connect to the MCP server.

  2. Use the scientific search tools:

Search Scientific

Search for scientific papers across different engines:

# Search arXiv for quantum computing papers
results = await mcp_scientific_search_search_scientific(
    query="quantum computing", 
    engine="arxiv"
)

# Search PubMed for COVID-19 research
results = await mcp_scientific_search_search_scientific(
    query="COVID-19 treatment", 
    engine="pubmed"
)

# Search Google Scholar for machine learning papers
results = await mcp_scientific_search_search_scientific(
    query="transformers neural networks", 
    engine="google_scholar"
)

# Search Semantic Scholar for AI ethics papers (via Tor)
results = await mcp_scientific_search_search_scientific(
    query="AI ethics", 
    engine="semantic_scholar"
)

Get URL Content

Extract content from a web page:

content = await mcp_scientific_search_get_url_content(
    url="https://example.com/research-paper"
)

Grep URL Content

Search for specific text patterns in a web page:

matches = await mcp_scientific_search_grep_url_content(
    url="https://example.com/research-paper",
    pattern="neural network"
)

Process PDF

Extract text and images from a PDF:

pdf_content = await mcp_scientific_search_process_pdf(
    url_or_path="https://example.com/paper.pdf",
    extract_images=True
)

Notes

  • Google Scholar searches may be rate-limited if used excessively. The implementation uses free proxies to reduce the risk of blocking.
  • PubMed requires an email address for usage tracking. Set the PUBMED_EMAIL environment variable or it will use a default.
  • Semantic Scholar searches are routed through Tor to avoid rate limits and IP blocking.
  • For best results, use specific search terms relevant to the domain.

Troubleshooting

  • Semantic Scholar Connection Issues: Make sure Tor is running on localhost:9050. If you experience issues, restart the Tor service.
  • Slow Responses: Tor routing may cause slower responses for Semantic Scholar searches.

License