gpt-researcher-mcp
Integrates with Google's generative AI (Gemini) to enable automated web research, summarization, and structured report generation.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@gpt-researcher-mcpresearch the impact of remote work on productivity"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
gpt-researcher-mcp MCP server
A MCP server for gpt-researcher
This is just a MCP wrapper for gpt-researcher.
This project, gpt-researcher-mcp, is a wrapper extension built on top of the open-source project gpt-researcher. The original gpt-researcher was developed by Assaf Elovic, and I am not the original author.
gpt-researcher is an automated research assistant that performs web searches, summarizes information, and generates structured reports based on a given query. This wrapper (gpt-researcher-mcp) is designed to make the original tool more suitable for integration into MCP or similar workflows.
Quickstart
Install
Claude Desktop
On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
"gpt-researcher-mcp": {
"command": "npx",
"args": ["-y", "gpt-researcher-mcp"],
"env": {
"llm_provider": "google_genai",
"GOOGLE_API_KEY": "your key",
"FAST_LLM": "google_genai:gemini-1.5-flash",
"SMART_LLM": "google_genai:gemini-1.5-pro",
"STRATEGIC_LLM":"google_genai:gemini-1.5-pro",
"EMBEDDING": "google_genai:models/text-embedding-004",
"TAVILY_API_KEY": "your key"
}
}Related MCP server: Gemini Research MCP Server
Development
To prepare the package for distribution:
Sync dependencies and update lockfile:
uv syncBuild package distributions:
uv buildThis will create source and wheel distributions in the dist/ directory.
Publish to PyPI:
uv publishNote: You'll need to set PyPI credentials via environment variables or command flags:
Token:
--tokenorUV_PUBLISH_TOKENOr username/password:
--username/UV_PUBLISH_USERNAMEand--password/UV_PUBLISH_PASSWORD
Debugging
Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.
You can launch the MCP Inspector via npm with this command:
npx @modelcontextprotocol/inspector uv run gpt-researcher-mcpUpon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
This server cannot be installed
Maintenance
Resources
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Looking for Admin?
If you are the server author, to access and configure the admin panel.
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