Doctree MCP

Name: Doctree MCP
Author: joesaby

by joesabyversion 1.0.1i★ –iRuns on your computer

Registry nameio.github.joesaby/doctree-mcp

Install

Overview

Description from the maker (original English)

BM25 search + tree navigation over markdown docs for AI agents. No embeddings, no LLM calls.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiVery new↓ 43/wk · ★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory
You need to fill in: DOCS_ROOT

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: DOCS_ROOT, DOCS_GLOB, DOCS_ROOTS, GLOSSARY_PATH

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "doctree": {
      "command": "npx",
      "args": [
        "-y",
        "doctree-mcp"
      ],
      "env": {
        "DOCS_ROOT": "your-value",
        "DOCS_GLOB": "your-value",
        "DOCS_ROOTS": "your-value",
        "GLOSSARY_PATH": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add doctree --env DOCS_ROOT=your-value --env DOCS_GLOB=your-value --env DOCS_ROOTS=your-value --env GLOSSARY_PATH=your-value -- npx -y doctree-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "doctree": {
      "command": "npx",
      "args": [
        "-y",
        "doctree-mcp"
      ],
      "env": {
        "DOCS_ROOT": "your-value",
        "DOCS_GLOB": "your-value",
        "DOCS_ROOTS": "your-value",
        "GLOSSARY_PATH": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "doctree": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "doctree-mcp"
      ],
      "env": {
        "DOCS_ROOT": "your-value",
        "DOCS_GLOB": "your-value",
        "DOCS_ROOTS": "your-value",
        "GLOSSARY_PATH": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

DOCS_ROOT required env
Path to your markdown repository root
DOCS_GLOB env
Glob pattern for finding markdown files (default: **/*.md)
DOCS_ROOTS env
Multiple weighted collections: ./docs:1.0,./api:0.8 (alternative to DOCS_ROOT)
GLOSSARY_PATH env
Path to glossary.json for query expansion (default: $DOCS_ROOT/glossary.json)

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account joesaby, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 5716 servers in this category
Published to the registry more recently than 3% of the other 5716 servers in this category
Basic checks equal to or better than 100% of the other 5716 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Doctree MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: DOCS_ROOT

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.1) reached the registry 9 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

by upstashWidely used↓ 972.7K/wk★ 64.2KUpdated 2 days ago

Computer or cloud

Install

Codebase Memory

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

by DeusDataWidely used↓ 18K/wk★ 48.1KUpdated 22 days ago

Runs on your computer

Install

Exa

Connect AI agents to Exa for web search, content fetching, and multi-step research.

by exa-labsWidely used★ 5.2KUpdated 2 months ago

Runs in the cloud✓ exa.ai

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

doctree-mcp

Agentic document retrieval over markdown, CSV, and JSONL. BM25 + tree navigation via MCP — no vector DB, no embeddings, no LLM calls at index time.

The pitch: MCP provides the structural primitives (a navigable tree, BM25, glossary, row lookup). The bundled skills provide the procedural knowledge (how to walk that tree). Together the agent behaves like a trained research librarian — not a one-shot searcher. See The Skill + MCP Pattern.

Quick Start

Have docs already? Point a client at them:

# In your AI tool's MCP config — see docs/CLIENTS.md for per-tool snippets

{ "mcpServers": { "doctree": { "command": "bunx", "args": ["doctree-mcp"], "env": { "DOCS_ROOT": "./docs", "WIKI_WRITE": "1" } } } }

Restart the tool → ask *"search the docs for X"* or invoke the doc-read prompt.

Starting fresh? Scaffold a Karpathy-style LLM wiki:

bunx doctree-mcp init          # configure current tool

bunx doctree-mcp init --all # configure every supported client bunx doctree-mcp init --dry-run

Creates docs/wiki/ (LLM-maintained) + docs/raw-sources/ (your inputs), writes the MCP config, installs a post-write lint hook, appends wiki conventions to CLAUDE.md / AGENTS.md / .cursor/rules/.

Operation Modes

Mode	Use when	Guide
stdio (default)	Local dev, agent on your machine	Client setup
HTTP (Streamable HTTP)	Teams, CI, hosted agents	Deployment — Railway · Fly · Render · Cloudflare Containers · Docker
CLI	`init`, `lint`, debug-index	Operation modes

Full decision tree: Operation Modes.

How It Works — Retrieve · Curate · Add

Agent: "How does token refresh work?"

→ search_documents("token refresh") #1 auth/middleware.md § Token Refresh Flow score: 12.4 #2 auth/oauth.md § Refresh Token Lifecycle score: 8.7

→ get_tree("docs:auth:middleware") [n1] # Auth Middleware [n4] ## Token Refresh Flow [n5] ### Automatic Refresh

→ navigate_tree("docs:auth:middleware", "n4") ← n4 + descendants

Core read tools (always on):

Tool	Purpose
`search_documents`	BM25 keyword search + facet filters + glossary expansion (markdown · CSV · JSONL)
`get_tree`	Table of contents — headings, word counts, summaries
`get_node_content`	Full text of a specific section by node ID
`navigate_tree`	A section plus all descendants in one call
`lookup_row`	O(1) exact-key lookup for structured data rows (e.g. `PROJ-44`)

Wiki write tools (opt-in with WIKI_WRITE=1):

Tool	Purpose
`find_similar`	Duplicate detection with overlap ratios
`draft_wiki_entry`	Scaffold: suggested path, inferred frontmatter, glossary hits
`write_wiki_entry`	Validated write: path containment, schema, duplicate guards, dry-run

Safety: path containment · frontmatter validation · duplicate detection · dry-run · overwrite protection.

Deprecated aliases (list_documents, find_files, find_symbol) are superseded by search_documents — still functional, no longer recommended.

The Skill + MCP Pattern

Most retrieval tools hand the agent a search box and hope for the best. doctree-mcp hands it a tree, and the bundled skills teach it how to walk one.

MCP = structural primitives. search_documents, get_tree, navigate_tree, get_node_content, lookup_row return tree positions the agent reasons over — not finished answers.
Skills = procedural knowledge. /doc-read, /doc-write, /doc-lint encode breadcrumb drill-down: search → outline → navigate → retrieve. The agent learns the *policy*, not just the API.

That pairing doesn't exist cleanly elsewhere:

Approach	Primitive	Skill teaches	Gap
Managed hybrid RAG (Cloudflare AI Search, Nia)	Flat chunks + similarity	—	Black-box score, no audit trail
Tool-returns-answer (Context7)	2 tools returning answers	Query shape	Agent can't reason about skipped content
Skill-over-CLI (QMD)	CLI over flat search	Query expansion	No tree to navigate
doctree-mcp + `/doc-read`	Navigable tree	Breadcrumbs, multi-instance routing, wiki compilation	—

Why iterative retrieval wins:

Context rot. Stuffing a 1M-token window with chunks degrades output. Breadcrumb navigation keeps working memory small.
Auditability. search_documents → get_tree → navigate_tree → get_node_content is a replayable trail. A cosine score is not. Regulated domains can ship the former.
Progressive disclosure. Fewer navigable primitives beat tool sprawl (cf. Cloudflare Code Mode).

Multi-instance = client-side federation. Register several doctree servers under different names; the /doc-read skill encodes the routing policy. Add or remove instances without touching the skill. See Client setup → Multi-instance routing.

The LLM Wiki Pattern

┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐

│ Raw Sources │ │ The Wiki │ │ The Schema │ │ (immutable) │ ──→ │ (LLM-maintained)│ ←── │ (you define) │ │ notes · logs │ │ runbooks · refs │ │ CLAUDE.md rules │ └─────────────────┘ └─────────────────┘ └─────────────────┘

Inspired by Karpathy's LLM Wiki. Full walkthrough: docs/LLM-WIKI-GUIDE.md.

Configuration (summary)

---

All non-reserved frontmatter fields become filter facets:

search_documents("auth", filters: { type: "runbook", tags: ["production"] })

Common env vars:

Variable	Default	Description
`DOCS_ROOT`	`./docs`	Docs folder
`DOCS_GLOB`	`*/.md`	Comma-separated globs (`*/.md,*/.csv,*/.jsonl`)
`DOCS_ROOTS`	—	Weighted multi-collection (`./wiki:1.0,./rfcs:0.5`)
`PORT`	`3100`	HTTP mode port
`WIKI_WRITE`	(unset)	`1` enables write tools
`GLOSSARY_PATH`	`$DOCS_ROOT/glossary.json`	Query-expansion glossary

Full reference: docs/CONFIGURATION.md.

Glossary — place glossary.json in docs root for bidirectional query expansion:

{ "CLI": ["command line interface"], "K8s": ["kubernetes"] }

Acronym definitions like "TLS (Transport Layer Security)" are also auto-extracted.

Structured data — CSV/JSONL files become documents where each row is a tree node. Column roles (id, title, description, facets, URL) are auto-detected from headers. See docs/STRUCTURED-DATA.md.

Running from Source

git clone https://github.com/joesaby/doctree-mcp.git

cd doctree-mcp && bun install

DOCS_ROOT=./docs bun run serve # stdio DOCS_ROOT=./docs bun run serve:http # HTTP (port 3100) DOCS_ROOT=./docs bun run index # CLI: inspect indexed output bun test

Performance

Operation	Time	Token cost
Full index (900 docs)	2–5s	0
Incremental re-index	~50ms	0
Search	5–30ms	~300–1K tokens
Tree outline	<1ms	~200–800 tokens

Docs

Setup & operation

Operation Modes — stdio · HTTP · CLI
Client Setup — Claude Code · Cursor · Windsurf · Codex · OpenCode · Claude Desktop
Deployment — Railway · Fly.io · Render · Cloudflare Containers · Docker
Configuration — env vars, frontmatter, ranking tuning

Patterns & concepts

LLM Wiki Guide — agent-maintained knowledge base walkthrough
Structured Data — CSV / JSONL indexing
Architecture & Design — BM25 internals, tree navigation
Competitive Analysis — PageIndex, QMD, GitMCP, Context7, managed RAG

Source

Prompts — MCP prompt templates
Skills: /doc-read · /doc-write · /doc-lint

Standing on Shoulders

[PageIndex](https://pageindex.ai) — hierarchical tree navigation
[Pagefind](https://pagefind.app) by CloudCannon — BM25 scoring, positional index, facets
[Bun.markdown](https://bun.sh) by Oven — native CommonMark parser
[Karpathy's LLM Wiki](https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f) — the LLM-maintained wiki pattern

License

MIT

Doctree MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

doctree-mcp

Quick Start

Operation Modes

How It Works — Retrieve · Curate · Add

The Skill + MCP Pattern

The LLM Wiki Pattern

Configuration (summary)

Running from Source

Performance

Docs

Standing on Shoulders

License