Model Context Protocol ( MCP ) server for Obsidian vault

This is side research and learning project, mostly focused on AI Agents and information retrivial, as well as evaluation of AI tools.

The server allows access to Obsidian.md Vault with search and read tools. Obsidian is the plain text Markdown editor, and keeps all note files in the single folder. The format makes it perfect companion and knowledge storage for AI Agents.

I do use combination of AI coding agent ( Claude Code, Cursor ) with Obsidian.md Vault since 2024, similar to Andrej Karpathy LLM Wiki, but a little bit more complicated with his proposal. With > 1500 notes, agents often miss important information, so I decided to create search tool that aware of knowledge organization that I use

Provided functionality

Web deep research

web_research tool is an AI agent similar by the functionality to Perplaxity.ai to answer questions based on the public information in Internet. It’s optimised to answer technical or academic questions. The core loop:

1. generate web search queries
2. fetch content from search results URLs. No attempts to bypass bot protections, but supports wide range of public sources: Arxiv.org articles, Github repositories, Reddit forums, Wikipedia, pdf documents - special cases to extract information from them, like switch to reddit API instead of read web pages, or use github raw format instead of html pages.
3. Use LLM to extract relevant information from fetch results, reduces main agent context
4. Reflection step that analyses result and decides to finish research or repeat loop to fill knowledge gaps
5. Final answer generator, creates short answer, long explanation how it was concluded, and relevant links to support answer

Evaluation results

Evaluation were performed with small models like Gamini Flash lite or GPT 5.4 nano to save costs, with fraction of questions. GAIA dataset - 60% on 20 questions DRACO dataset - around 40%, mostly because answers are less detailed than expected in evaluation criteria

Evaluation code not in this repository, it is part of internal project for team wide AI Software development tools, created to optimize process for my startup Jobsflow.ai. The tool ported from that project.

Obsidian Vault RAG

obsidian_search is hybrid vector + BM25 search engine, mostly classical RAG. It optimized to Vault organization that I use

Note format assumption

I do keep all notes with the same pattern, and indexing tool uses expected format to split note into chunks and generate additional metadata. The format enforced by special Claude Code skill that used to process all new nortes.

1. Frontmatter properties:
   1. title - short sentence what is it about