Skip to main content

Git-backed multi-user wiki MCP server — LTM for any AI

Project description

PyPI version License: MIT

wikimcp

Long-term memory for AI — a git-backed personal wiki that any AI client can read and write to.

Inspired by Andrej Karpathy's LLM Wiki pattern.


Why this exists

Most people's experience with AI and documents is RAG: upload files, the AI retrieves chunks at query time, generates an answer. The AI rediscovers knowledge from scratch on every question. Nothing accumulates.

wikimcp is different. Instead of retrieving from raw documents each time, the AI incrementally builds and maintains a personal wiki — a structured, interlinked collection of markdown files. When you discuss a topic, the AI doesn't just respond — it updates topic pages, creates entity entries, cross-references related concepts, and logs what happened. The knowledge is compiled once and kept current, not re-derived every session.

The wiki is a persistent, compounding artifact. Cross-references are already there. Contradictions get flagged. The synthesis reflects everything you've ever discussed. It keeps getting richer with every conversation.

You never write the wiki yourself — the AI writes and maintains all of it. You curate sources, direct the analysis, and ask good questions. The AI does all the bookkeeping — summarising, cross-referencing, filing, and maintenance.


How it works

Three layers:

  1. Raw sources (raw/) — your documents. Articles, papers, notes. The AI reads from these but never modifies them.
  2. The wiki (wiki/) — AI-generated markdown files. Topic pages, entity pages, chat summaries, the index. The AI owns this layer entirely.
  3. The schema (CLAUDE.md) — tells the AI how the wiki is structured and what workflows to follow. Delivered automatically at the start of every session via wiki_info.

The AI performs three operations:

  • Ingest — you drop a source into raw/, the AI reads it, extracts key information, creates/updates wiki pages, updates the index and log. A single source can touch 10-15 pages.
  • Query — you ask a question, the AI reads the index, navigates to relevant pages, synthesises an answer. Good answers get filed back into the wiki as new pages.
  • Lint — periodically health-check for contradictions, orphan pages, stale claims, missing cross-references.

Every write is auto-committed to git. Full history, branching, and remote sync.


Use cases

  • Personal knowledge — goals, health, self-improvement, journal entries, article notes. Build a structured picture of yourself over time.
  • Research — go deep on a topic over weeks. Read papers, articles, reports. The wiki builds a comprehensive synthesis with an evolving thesis.
  • Reading a book — file each chapter, build pages for characters, themes, plot threads. By the end you have a rich companion wiki.
  • Work — meeting notes, project decisions, team knowledge. The wiki stays current because the AI does the maintenance nobody wants to do.
  • Learning — course notes, concept maps, practice problems. Knowledge accumulates instead of fading.

Quick start

pip install wikimcp

Set up the wiki

# Default location: ~/llm-wiki
wikimcp init

# Or pick your own directory
wikimcp init --wiki-dir ~/my-wiki

This creates the wiki folder structure, initialises a git repo, and prints a JSON config snippet.

Connect to Claude Desktop

Copy the printed JSON and paste it into your Claude Desktop config:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Linux: ~/.config/Claude/claude_desktop_config.json

The snippet looks like:

{
  "mcpServers": {
    "wikimcp": {
      "command": "wikimcp",
      "args": ["serve", "--wiki-dir", "/Users/you/my-wiki"]
    }
  }
}

Restart Claude Desktop.

Start using it

Open a new Claude conversation. The AI will call wiki_info at the start and receive the full wiki schema with workflow instructions.

Just have a normal conversation — discuss a topic, share an idea, ask the AI to process a document. At the end of the session, the AI should automatically:

  • Create/update topic and entity pages
  • Write a chat summary
  • Append to the activity log
  • Update the index

If it doesn't do this automatically, tell Claude: "update the wiki with what we discussed" — or add this to your Claude Desktop system prompt for hands-free operation:

You have a wiki connected via MCP. Call wiki_info at the start of every conversation. At the end, update relevant wiki pages, write a chat summary, append to the log, and update the index.

Browse in Obsidian

Open your wiki folder in Obsidian. You'll see every page the AI creates in real time — topics, entities, chat summaries, the index. Use Obsidian's graph view to see how everything connects.


Sync with GitHub

The wiki is a git repo from the start. To back it up to GitHub:

cd ~/my-wiki
gh repo create my-wiki --private --source=. --remote=origin --push

Then push periodically:

cd ~/my-wiki && git push

Or set up a cron job to auto-push every 5 minutes:

# add to crontab -e
*/5 * * * * cd ~/my-wiki && git push origin main 2>/dev/null

Wiki folder structure

~/my-wiki/
  CLAUDE.md              ← schema and workflow guide (AI reads this at session start)
  wiki/
    index.md             ← master catalog of all pages
    log.md               ← append-only activity log
    chats/               ← one page per conversation
    topics/              ← concept and topic pages
    entities/            ← people, tools, projects
  raw/                   ← your source documents (AI never modifies these)
  .git/                  ← full git history

MCP tools

11 tools exposed to any MCP-compatible AI client:

Tool Arguments Description
wiki_info Wiki stats + full schema instructions. Called at session start.
read_index Read wiki/index.md — the master catalog.
update_index content Overwrite wiki/index.md and auto-commit.
write_page path, content Create or overwrite a wiki page and auto-commit.
read_page path Read a wiki page.
list_pages subdirectory? List all pages (or a subdirectory).
search_wiki query, case_sensitive? Full-text search across all pages.
search_pages query, limit? Rank wiki pages by relevance and return compact snippets.
retrieve_context query, limit? Return contextual snippets from the most relevant pages.
append_log entry, operation? Append timestamped entry to wiki/log.md and auto-commit.
delete_page path Delete a wiki page and auto-commit.

Every write triggers an auto git commit with author wikimcp-bot <wikimcp@localhost>.


Server mode (multi-user)

For teams or hosting wikis for multiple people on a VPS.

Setup

# 1. Install
pip install wikimcp

# 2. Initialise server
wikimcp server init --dir /data/wikimcp --port 8765

# 3. Add users
wikimcp add-user alice --dir /data/wikimcp
wikimcp add-user bob   --dir /data/wikimcp

# 4. Start server
wikimcp server start --dir /data/wikimcp

# 5. (Optional) Install as system service
sudo wikimcp install-service --dir /data/wikimcp --port 8765

What you get

  • MCP endpoint: http://host:port/mcp (bearer-token auth)
  • Web reader: http://host:port/wiki/<username> (read-only HTML UI)
  • Git hosting: http://host:port/git/<username> (clone/push over HTTP)
  • Health check: http://host:port/health

User config

Each user configures their AI client with:

{
  "mcpServers": {
    "wikimcp": {
      "url": "https://yourserver.com/mcp",
      "headers": { "Authorization": "Bearer wikimcp_alice_<token>" }
    }
  }
}

Auth

Bearer token per user. Tokens stored as SHA-256 hashes — never plaintext. Manage with wikimcp add-user, remove-user, rotate-token, list-users.


CLI reference

wikimcp init [--wiki-dir ~/llm-wiki]
wikimcp serve [--wiki-dir] [--transport stdio|http] [--host] [--port] [--allowed-host ...] [--allow-any-host]

wikimcp server init [--dir /data/wikimcp] [--port 8765]
wikimcp server start [--dir] [--port] [--host] [--allowed-host ...] [--allow-any-host]
wikimcp server stop
wikimcp server status [--dir]

wikimcp add-user <username> [--dir]
wikimcp remove-user <username> [--dir]
wikimcp list-users [--dir]
wikimcp rotate-token <username> [--dir]

wikimcp remote add <username> <remote-name> <git-url> [--dir]
wikimcp remote remove <username> <remote-name> [--dir]
wikimcp remote list <username> [--dir]
wikimcp remote push <username> [--remote <name>] [--dir]

wikimcp export <username> [--format zip|tar] [--out ./] [--dir]
wikimcp install-service [--dir] [--port]

Transport modes

Transport Command Used by
stdio wikimcp serve (default) Claude Desktop, LM Studio, Gemini CLI, Claude Code
HTTP wikimcp serve --transport http ChatGPT, claude.ai (via ngrok)
HTTP wikimcp server start All clients (always-on multi-user server)

Host header allowlist (HTTP transport)

The MCP SDK enforces DNS-rebinding protection on the streamable-HTTP transport: by default it accepts the Host header only when it is localhost or 127.0.0.1 (with any port). Any other host — including host.docker.internal from a client running in a Docker container — is rejected with HTTP 421 "Invalid Host header".

To allow additional hosts, pass --allowed-host (repeatable) to wikimcp serve or wikimcp server start:

# Allow a LibreChat / Docker client connecting via host.docker.internal
wikimcp serve --transport http --host 0.0.0.0 --port 8765 \
    --wiki-dir ~/llm-wiki \
    --allowed-host host.docker.internal --allowed-host 100.85.70.2

On a fully trusted/isolated network you can disable the check entirely with --allow-any-host. Security note: --allow-any-host turns off host/origin validation completely — only use it behind a firewall or VPN, never on a host exposed to untrusted networks.

Upgrade note: Versions before 0.1.5 had a different (and in some deployments hot-patched) host policy. Starting in 0.1.5 the default is localhost-only, so if you connect from a non-localhost client you must add --allowed-host <that-host> (or --allow-any-host). Operators upgrading an existing deployment must update their launch command — e.g. the systemd ExecStart:

wikimcp serve --transport http --host 0.0.0.0 --port 8765 \
    --wiki-dir /home/ubuntu/wikimcp-data/users/mohith \
    --allowed-host host.docker.internal --allowed-host 100.85.70.2

Dependencies

Package Purpose
mcp[cli] FastMCP — MCP server framework
fastapi Web reader + HTTP transport
uvicorn ASGI server
jinja2 HTML templates
click CLI framework
gitpython Git operations
rich Terminal formatting
markdown Markdown-to-HTML rendering

Credits

Based on the LLM Wiki pattern by Andrej Karpathy — the idea that LLMs should incrementally build and maintain a persistent wiki rather than re-deriving knowledge on every query.

License

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

wikimcp-0.1.6.tar.gz (53.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

wikimcp-0.1.6-py3-none-any.whl (52.7 kB view details)

Uploaded Python 3

File details

Details for the file wikimcp-0.1.6.tar.gz.

File metadata

  • Download URL: wikimcp-0.1.6.tar.gz
  • Upload date:
  • Size: 53.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.20

File hashes

Hashes for wikimcp-0.1.6.tar.gz
Algorithm Hash digest
SHA256 8285eb9fdccbc2117ace53741d99ab26955e6ddd1922b4bb8934c548ea1999e7
MD5 bf988d8568d3849f36b85072253f800b
BLAKE2b-256 c4a5ad9282f55be3f7156febe577fb42591165e8bec195d6ce438859978e7353

See more details on using hashes here.

File details

Details for the file wikimcp-0.1.6-py3-none-any.whl.

File metadata

  • Download URL: wikimcp-0.1.6-py3-none-any.whl
  • Upload date:
  • Size: 52.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.20

File hashes

Hashes for wikimcp-0.1.6-py3-none-any.whl
Algorithm Hash digest
SHA256 8b2b95b702d2a0d5960061264b7be14aec74ba209ac0459ffe32ab96173c35db
MD5 d0ec903f1d64c40e0c03e214c6b7d9ec
BLAKE2b-256 2a0187bd2d302b8cac5a3005a22c999e5ec95b6d78f31b6918565f8d02ecb944

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page