1. Conduid
  2. RAG
  3. Obsidian LLM Wiki
MCP server · RAG

Obsidian LLM Wiki

Convert your Obsidian markdown vault into a six-persona MCP team for local LLM tools to provide cited, accurate insights.

34Low

Scored 28 days ago · breakdown

About Obsidian LLM Wiki

Obsidian LLM Wiki is an MCP server in the RAG category: convert your Obsidian markdown vault into a six-persona MCP team for local LLM tools to provide cited, accurate insights.

The repository has 1 stars and 0 forks.

Install

From source
git clone https://github.com/2233admin/obsidian-llm-wiki

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Tools (6)

vault.daily`Daily/YYYY-MM-DD.md`

Parameters not published.

vault.decide`Decisions/YYYY-MM-DD--{slug}.md`

Parameters not published.

vault.ingest`00-Inbox/{slug}.md`

Parameters not published.

vault.meeting`Meetings/YYYY-MM-DD--{slug}.md`

Parameters not published.

vault.person`People/{name}.md`

Parameters not published.

vault.project`Projects/{name}.md`

Parameters not published.

Ask AI

✦

Ask AI about Obsidian LLM Wiki

Powered by Claude · Grounded in docs

I know everything about Obsidian LLM Wiki. Ask me about installation, configuration, usage, or troubleshooting.

Security checks

  • ✓README presentThe repository ships documentation.

5 checks have not been run yet.

README

LLM Wiki Bridge

Your markdown vault, compiled into a 6-persona MCP team for Claude Code, Codex, OpenCode, and Gemini CLI. Headless-first. Cites, doesn't guess.

MCP Wiki

Language: English (this page) · 简体中文 — Guide: English · 简体中文 — Wiki: Home · Architecture · Rationale · FAQ

demo

You have 500 markdown notes. You forget half of them. Your AI agent cannot read them -- it paraphrases from its context window and fabricates citations. Every morning you spend 20 minutes re-finding what you already knew.

LLM Wiki Bridge is a headless-first MCP server that compiles your vault -- wikilinks, aliases, tags, frontmatter -- into a concept graph your agent calls directly. The agent doesn't guess. It calls vault.search, reads the cited notes with vault.read, answers with evidence. Obsidian is optional at runtime; the filesystem adapter is always available.

Inspired by Andrej Karpathy's LLM Wiki. Markdown is the source of truth; the compiler turns structure into a graph; MCP exposes it.


Quick start (30 seconds)

git clone --depth 1 https://github.com/2233admin/obsidian-llm-wiki.git
cd obsidian-llm-wiki && ./setup                      # --host claude | codex | opencode | gemini

Windows (PowerShell):

git clone --depth 1 https://github.com/2233admin/obsidian-llm-wiki.git
cd obsidian-llm-wiki; .\setup.ps1

The setup script extracts a 1.6 MB skill bundle into your host's skills directory, prints the .mcp.json snippet to paste into your agent config, and exits. After restart, your agent picks up the new MCP server and the six /vault-* personas. The cloned repo can then be deleted — the installed skill is self-contained. If the one-liner breaks, docs/INSTALL.md has the per-host paths and the manual recipe.


Works with

Any MCP-compatible host:

Host Command Status
Claude Code ./setup --host claude primary target, fully exercised
Codex CLI ./setup --host codex path configured, smoke-tested
OpenCode ./setup --host opencode path configured, smoke-tested
Gemini CLI ./setup --host gemini path configured, smoke-tested

Anything else speaking stdio MCP transport should work — the setup script only copies skills into the right directory and prints the .mcp.json snippet. If your host reads MCP config from somewhere else, paste the snippet there by hand.


Example prompts

Cold start -- no vault context:

/vault-librarian what do I know about attention heads

Warm start -- specify a note you have:

/vault-librarian explain [[retrieval-augmented-generation]] in the context of my other notes on LLMs

Format-specific -- you want a list, not prose:

/vault-historian what decisions did I make about training data between January and March 2026

Iterate -- refine an answer:

/vault-curator find all orphan notes and stale notes in my vault that have not been updated in 90 days

Six personas, one MCP surface

Each persona is an opinionated prompt over the same 40-operation MCP tool set.

Name What it does Primary MCP tools
vault-librarian reads, searches, cites from the vault vault.search, vault.read, vault.list
vault-architect compiles concept graph, suggests refactors vault.graph, vault.backlinks, compile.run
vault-curator finds orphans, dead links, duplicates, stale notes vault.lint, vault.searchByTag, vault.search
vault-teacher explains a note in context of its neighbors vault.backlinks, vault.read, vault.graph
vault-historian answers what you were thinking on date X vault.searchByFrontmatter, vault.stat, vault.search
vault-janitor proposes cleanups, dry-run by default vault.lint, vault.delete (dry), vault.rename (dry)

How it works (30-second tour)

Your markdown files -- with wikilinks [[like this]], aliases, frontmatter tags, and mtime -- are the source of truth. The compiler runs once and produces a concept graph (nodes = notes, edges = links and semantic relationships). The MCP server exposes this graph as tools: vault.search, vault.backlinks, vault.graph, and 40+ more.

When Claude Code (or any MCP-compatible agent) runs /vault-librarian, it calls vault.search and vault.read directly. The agent gets citations -- not guesses.

  • No embeddings required at small scale. Optional pgvector-backed semantic search via the memU adapter.
  • No database. Filesystem-only by default; a compiled graph is cached as plain JSON alongside the vault.
  • No Obsidian required at runtime. The filesystem adapter is always available. Obsidian is an optional adapter if you want live plugin-API features via a WebSocket bridge.

Deep dives

The wiki has the long-form answers. Eight pages, any order.

Page Answers
Rationale Why this exists. Why not just grep, not just an Obsidian plugin, not just a vector DB, not just a long-context LLM. Covers the product drift.
Architecture Four-layer system diagram. Request lifecycle (8 steps, /vault-librarian to cited answer). Extension points.
Adapter-Spec Adapter contract, capability matrix, fan-out and ranking, failure modes, recipe for a fifth adapter.
Compile-Pipeline What each stage produces, where the graph lives on disk, performance reference points.
Persona-Design Six user-facing personas vs seventeen underlying skills. The design discipline that keeps them from collapsing into one generic agent.
Security-Model Dry-run default, protected paths, preflight gates, bearer-token transport, what this explicitly does not secure.
Recipes Content collectors (Feishu, Gmail, Linear, X, WeChat, and more) that land external sources into the vault.
FAQ Does it need Obsidian running? How big a vault? Why dry-run? First-draft answers, expands as questions come in.

Limits

  • Does not understand code in your notes -- it indexes text, wikilinks, and structure. For AST-level code reasoning, enable the optional gitnexus adapter.
  • Does not sync bidirectionally with Obsidian in real time -- the WebSocket adapter requires Obsidian to be running.
  • Does not replace a vector database for semantic similarity at scale -- enable the optional memU adapter for that.
  • The split between this repo (headless MCP) and its sibling obsidian-vault-bridge (Obsidian plugin) is still settling. See the Rationale page for the drift discussion.

License

GPL-3.0. See LICENSE.

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Obsidian LLM Wiki

How do I install Obsidian LLM Wiki?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Obsidian LLM Wiki safe to use with an AI agent?

Its trust score is 34 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Obsidian LLM Wiki still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.