ResearchMCP is a research tool that combines MCP with search APIs like Brave and Tavily, enabling deep research capabilities similar to ChatGPT's DeepResearch. It supports web searching, caching, and MCP protocol compliance to assist researchers and developers.
Added on:
Created by:
Apr 03 2025
ResearchMCP is a research tool that combines MCP with search APIs like Brave and Tavily, enabling deep research capabilities similar to ChatGPT's DeepResearch. It supports web searching, caching, and MCP protocol compliance to assist researchers and developers.
Added on:
Created by:
Apr 03 2025
Ryo Ichinose
Featured
What is ResearchMCP?
ResearchMCP is a sophisticated research tool built using Deno and the Hono framework, designed to facilitate advanced web-based research. It integrates with search engines like Brave Search and Tavily Search through their APIs, leveraging the Model Context Protocol (MCP) to structure interactions. The system offers caching for search results to enhance performance and reduce API calls. It is deployable via Docker and has features supporting MCP protocol compliance, making it suitable for developers, researchers, and data analysts aiming for comprehensive web research with structured context management and seamless API integration.
Who will use ResearchMCP?
- Researchers
- Developers
- Data Analysts
- Academic Institutions
How to use the ResearchMCP?
- Step1: Install Deno and clone the ResearchMCP repository.
- Step2: Set environment variables including API keys for Brave and Tavily Search.
- Step3: Run the application locally using provided Makefile commands or deploy with Docker.
- Step4: Use the MCP server for research tasks through compatible clients like Claude Desktop.
- Step5: Configure MCP server connection in your client with the appropriate command and environment settings.
ResearchMCP's Core Features & Benefits
The Core Features
- Web Search using Brave and Tavily APIs
- MCP Protocol Compliance
- Result Caching
- Docker Deployment
The Benefits
- Enables structured and efficient web research
- Reduces API call volume through caching
- Supports multiple search engines
- Deployable in various environments for flexibility
ResearchMCP's Main Use Cases & Applications
- Academic research automation
- Data collection for machine learning datasets
- Web content analysis
- Research-oriented chatbot integration
FAQs of ResearchMCP
Developer
- riii111
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