Ratatoskr-mcp

A high-performance MCP (Model Context Protocol) server that retrieves Wikipedia articles from local multistream dump files — no database, no ingest step, no internet required at query time.

Named after Ratatoskr, the squirrel of Norse mythology who runs up and down the world tree Yggdrasil carrying messages between realms. Fast, persistent, and always delivering knowledge.

What it does

Exposes a single MCP tool — get_wikipedia_article(topic) — that takes a Wikipedia article title and returns its content as Markdown: title, lead-section body, and infobox.

A typical request completes in 0.3–0.6 seconds. The tool follows MediaWiki redirects automatically (e.g., "Einstein" resolves to "Albert Einstein"), and uses fuzzy matching as a fallback when exact title matching fails.

How it works

topic ──▶ ripgrepy (case-insensitive fixed-string search of 1.2GB index)
      ──▶ exact match? ──▶ yes ──▶ fetch page from bz2 dump
                         ──▶ no  ──▶ cluster hits by byte_offset
                                   ──▶ rapidfuzz word-boundary scoring
                                   ──▶ best fuzzy match ──▶ fetch page
      ──▶ decompress bz2 block (bz2 module)
      ──▶ parse XML (lxml) ──▶ redirect? ──▶ follow chain (max depth 5)
                             ──▶ parse wikitext (mwparserfromhell)
                             ──▶ extract lead section + infobox
      ──▶ Markdown output

No database to build. No ingest step. The server searches Wikipedia's multistream index text file directly using ripgrep, and decompresses only the relevant bz2 block on demand.

Quick start

Prerequisites

• Docker and Docker Compose
• ~26 GB disk space for the Wikipedia dump files

1. Clone

git clone https://github.com/edk4971/Ratatoskr-mcp.git
cd Ratatoskr-mcp

2. Download the dump files

Download the latest English Wikipedia multistream dump into the dumps/ directory:

https://meta.wikimedia.org/wiki/Data_dump_torrents#English_Wikipedia

Then rename (or symlink) the files to the names the compose file expects:

bunzip enwiki-<DATE>-pages-articles-multistream-index.txt.bz2
ln -s enwiki-<DATE>-pages-articles-multistream-index.txt multistream-index.txt
ln -s enwiki-<DATE>-pages-articles-multistream.xml.bz2 multistream.xml.bz2

3. Run

docker compose up -d

The server will be available at http://localhost:8000.

Configuration

All settings are controlled via environment variables (set in docker-compose.yaml):

Variable	Default	Description
MCP_HOST	0.0.0.0	Host address to bind
MCP_PORT	8000	Port to listen on
INDEX_PATH	/data/multistream-index.txt	Path to the multistream index text file
DUMP_PATH	/data/multistream.xml.bz2	Path to the multistream bz2 dump file

Performance

Benchmarked with 15 diverse Wikipedia articles through the MCP server (SSE transport):

Article	Time	Size
Burj Khalifa	0.37s	3,938 chars
Nikola Tesla	0.51s	4,021 chars
Hubble Space Telescope	0.51s	5,640 chars
Isaac Newton	0.60s	7,527 chars
Leonardo da Vinci	0.53s	4,177 chars
Kyoto	0.40s	7,622 chars

All requests completed in under 1 second, well within the sub-3-second target. Times include index lookup, bz2 decompression, XML parsing, wikitext extraction, and redirect resolution.

Using with an MCP client

The server speaks the MCP protocol over SSE. Point any MCP-compatible client at:

http://localhost:8000/sse

The single exposed tool is:

• get_wikipedia_article(topic: str) -> str — Returns the article as Markdown, or an error message if not found.

Project structure

├── server.py          — MCP server entry point (fastmcp, SSE transport)
├── index.py           — Flat-file index search (ripgrepy + rapidfuzz)
├── retrieval.py       — bz2 block fetching + output assembly + redirect following
├── parser.py          — Wikipedia XML/wikitext parsing (lxml + mwparserfromhell)
├── Dockerfile
├── docker-compose.yaml
└── requirements.txt

Running without Docker

Requires Python 3.12+ and ripgrep installed on the system.

pip install -r requirements.txt

# Set paths to your dump files
export INDEX_PATH=./dumps/enwiki-20260601-pages-articles-multistream-index.txt
export DUMP_PATH=./dumps/enwiki-20260601-pages-articles-multistream.xml.bz2

python server.py

License

UNLICENSE