🔎 GPT Researcher

Name: 🔎 GPT Researcher
Author: assafelovic

@assafelovic

代码仓库主页

关于 🔎 GPT Researcher

An autonomous agent that conducts deep research on any data using any LLM providers

#python #search #agent #automation #research #ai #mcp #webscraping #llms #mcp-server #deepresearch

基本信息

分类

AI 与智能体

许可证

Apache-2.0

运行时

python

传输方式

stdio

发布者

assafelovic

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "gpt-researcher": {
      "command": "npx",
      "args": [
        "skills",
        "add",
        "assafelovic/gpt-researcher"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is 🔎 GPT Researcher?

GPT Researcher is an open deep research agent designed for web and local research on any given task. It produces detailed, factual, unbiased research reports with citations and addresses misinformation, speed, determinism, and reliability. The server integrates with MCP clients like Claude to extend deep research capabilities.

How to use 🔎 GPT Researcher?

Install via pip (pip install gpt-researcher) or clone the repository, set OPENAI_API_KEY and TAVILY_API_KEY environment variables, then run python -m uvicorn main:app --reload. To use as a Claude Skill, run npx skills add assafelovic/gpt-researcher. For MCP integration, set RETRIEVER=tavily,mcp and pass mcp_configs to GPTResearcher.

Key features of 🔎 GPT Researcher

Generate detailed research reports using web and local documents.
Smart image scraping and AI-generated inline images.
Aggregate over 20 sources for objective conclusions.
Deep Research with tree-like exploration and concurrent processing.
JavaScript-enabled web scraping and memory/context maintenance.
Export reports to PDF, Word, and other formats.

Use cases of 🔎 GPT Researcher

Conduct objective research on any topic with cited sources.
Combine web search with local documents for tailored reports.
Integrate deep research into AI assistants like Claude.
Automate generation of long-form reports (>2,000 words) with inline visuals.

FAQ from 🔎 GPT Researcher

What API keys are required?

You need OPENAI_API_KEY and TAVILY_API_KEY. For AI-generated images, also set GOOGLE_API_KEY and IMAGE_GENERATION_ENABLED=true. Optional keys are LANGCHAIN_API_KEY and GITHUB_TOKEN for MCP GitHub integration.

Can I use local or custom LLM models?

Yes, set OPENAI_BASE_URL to your custom API base URL (e.g., for local models or other providers). Deep Research uses models like o3-mini by default.

Does 🔎 GPT Researcher support MCP?

Yes, it supports MCP integration via the RETRIEVER=tavily,mcp environment variable. You can connect to data sources like GitHub repositories, databases, and custom APIs by providing mcp_configs.

How long does a deep research task take?

Deep Research takes approximately 5 minutes per research and costs about $0.4 per research using o3-mini with "high" reasoning effort, as stated in the documentation.

Can I research local documents?

Yes, set DOC_PATH to the folder containing your documents (PDF, plain text, CSV, Excel, Markdown, PowerPoint, Word) and select "My Documents" in the frontend or set report_source to "local" in the PIP package.

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