scholar-mcp-server-sse 0.1

MCP Server (SSE) for searching via DuckDuckGo and Google Scholar

Scholar Search MCP Server (SSE)

A Model Context Protocol (MCP) server that provides web search capabilities through DuckDuckGo and Google Scholar, with additional features for content fetching and parsing, running over HTTP (SSE).

Features

• Web Search: Search DuckDuckGo and Google Scholar with advanced rate limiting and result formatting
• Content Fetching: Retrieve and parse webpage content with intelligent text extraction
• Rate Limiting: Built-in protection against rate limits for both search and content fetching
• Error Handling: Comprehensive error handling and logging
• LLM-Friendly Output: Results formatted specifically for large language model consumption

Usage

Installation

You can install the server using pip:

pip install scholar-mcp-server-sse

Startup

You can start the server using the following command:

scholar-mcp-server-sse --host <your-host> --port <your-port>

• --host: The host to bind the server to. Defaults to 0.0.0.0.
• --port: The port to run the server on. Defaults to 8000.

For example:

duckduckgo-mcp-server-sse --host 127.0.0.1 --port 8080

Settings in CLINE

Add the following configuration, adjusting the host and port to match your server setup:

{
    "mcpServers": {
        "scholar-search-sse": {
            "disabled": false,
            "timeout": 60,
            "type": "sse",
            "url": "http://127.0.0.1:8000/sse",
            "headers": {
                "Accept": "application/json, text/event-stream"
            }
        }
    }
}

Available Tools

1. Search Tool

async def search(query: str, max_results: int = 10) -> str

Performs a web search on DuckDuckGo and returns formatted results.

Parameters:

• query: Search query string
• max_results: Maximum number of results to return (default: 10)

Returns: Formatted string containing search results with titles, URLs, and snippets.

2. Content Fetching Tool

async def fetch_content(url: str) -> str

Fetches and parses content from a webpage.

Parameters:

• url: The webpage URL to fetch content from

Returns: Cleaned and formatted text content from the webpage.

3. Scholar Search Tool

async def scholar_search(query: str, max_results: int = 10, year_low: int = None, year_high: int = None, sort_by: str = 'relevance', start_index: int = 0) -> str

Performs a search on Google Scholar and returns formatted results.

Parameters:

• query: Search query string
• max_results: Maximum number of results to return (default: 10)
• year_low: Minimum year of publication (optional)
• year_high: Maximum year of publication (optional)
• sort_by: Sort by 'relevance' or 'date' (default: 'relevance')
• start_index: Starting index of the result list (default: 0)

Returns: Formatted string containing search results with titles, authors, publication details, and summaries.

Features in Detail

Rate Limiting

• Search: Limited to 30 requests per minute
• Content Fetching: Limited to 20 requests per minute
• Automatic queue management and wait times

Result Processing

• Removes ads and irrelevant content
• Cleans up DuckDuckGo redirect URLs
• Formats results for optimal LLM consumption
• Truncates long content appropriately

Error Handling

• Comprehensive error catching and reporting
• Detailed logging through MCP context
• Graceful degradation on rate limits or timeouts

Contributing

Issues and pull requests are welcome! Some areas for potential improvement:

• Additional search parameters (region, language, etc.)
• Enhanced content parsing options
• Caching layer for frequently accessed content
• Additional rate limiting strategies

License

This project is licensed under the MIT License.