GPT Researcher vs seekstone
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.; seekstone: Seekstone is an Obsidian Model Context Protocol (MCP) server that provides AI agents like Claude direct read and write access to your Obsidian vault. It operates filesystem-direct, eliminating the need for the Obsidian app or its Local REST API plugin, offering significantly faster search and drastically reduced context window usage compared to other MCP servers.
TL;DR
- 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.
AI agents searching Obsidian notes for specific topics and summarizing information.
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