How does Deep Research protect my privacy?
All data is processed and stored locally in your browser. When using the local API mode, no API keys or server-side configurations are needed.
@u14app
Basic information
Use any LLMs (Large Language Models) for Deep Research. Support SSE API and MCP server.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"deep-research": {
"command": "docker",
"args": [
"pull",
"xiangfa/deep-research:latest"
]
}
}
}Tool list not available yet
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Deep Research is an open-source AI-powered tool that generates in-depth research reports in about two minutes. It supports multiple large language models and search engines, processes and stores all data locally in the browser to protect user privacy, and can be deployed on Vercel, Cloudflare, Docker, or as a static site.
Use the free Gemini model by obtaining a Gemini API key, then deploy the project with a one-click button to Vercel or Cloudflare, and start using. For other LLMs, set the LLM API key and optional API base URL after deployment. For local development, clone the repository, install dependencies with pnpm, set environment variables via env.tpl, and run pnpm dev.
All data is processed and stored locally in your browser. When using the local API mode, no API keys or server-side configurations are needed.
It supports Gemini, OpenAI, Anthropic, Deepseek, Atlas Cloud, Grok, Mistral, Azure OpenAI, OpenAI-compatible LLMs, OpenRouter, Ollama, etc. For search, it supports Searxng, Tavily, Firecrawl, fastCRW, Exa, Bocha, Brave, and others.
Yes, you can deploy it on Vercel, Cloudflare Pages, using Docker, or as a static export. Detailed guides are provided for each method.
Yes, it provides a Server-Sent Events (SSE) API and a Model Context Protocol (MCP) server. You can use the SSE API to start research tasks and receive real-time results.
Yes, Deep Research is MIT licensed and freely available for personal and commercial use.

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