Hatchdoor vs GPT Researcher
Hatchdoor: Hatchdoor is an agent-native, self-hosted web app for managing Obsidian-style Markdown vaults, offering a fast web UI for browsing, searching, and editing notes. It provides AI agents with first-class access to the vault via the Model Context Protocol (MCP) for reading, searching, creating, and editing notes safely. Your Markdown files remain the source of truth, with Hatchdoor building a disposable SQLite read model for performance and features like keyword and semantic search.; GPT Researcher: GPT Researcher is an open-source LLM agent designed for deep, structured research on any topic using web and local sources. It produces detailed reports with citations by running parallel research agents, scraping relevant sources, filtering content, and synthesizing findings. Supports local document research, customizable report formats, and multiple LLM backends including OpenAI, Anthropic, and Ollama.
TL;DR
Individuals or teams with a folder of Markdown notes needing a private web interface.
- You want an Apache-2.0 agent that plans sub-questions, searches the web and local documents in parallel, and writes 2,000+ word reports with citations.
- You want to use it as a Python library, standalone web app, or MCP-connected research skill with PDF/Word export.
- You want a general-purpose super-agent harness with a bash sandbox, persistent memory, and Feishu/WeCom/Slack bots; DeerFlow is built for that.
- You do not want per-report search API (e.g. Tavily) and multi-call LLM token costs.
Side-by-Side Comparison
Features
Use Cases
Best For
FAQ
Deploy on DigitalOcean
Host your MCP servers, Docker containers, and AI agents with $200 free credit over 60 days.