Legal Search MCP

Korean case law, statutes and sentencing data as MCP tools. Point an AI client at it and the model can look up statute text as it stood on a given date, find judgments by the facts of a case, read one judgment and answer a question about it, and compute a sentencing range the way a Korean court does.

Five read-only tools:

This is the production system behind 법률AI, and the descendant of the research prototype in legal_mcp — see Paper.

Quick start — hosted

The full corpus (190k+ judgments, statutes with their amendment history, administrative rules, sentencing guidelines) is served for you. Get a free key at console.crow-tit.com and add:

{
  "mcpServers": {
    "legal-search": {
      "type": "http",
      "url": "https://mcp.crow-tit.com/mcp",
      "headers": { "Authorization": "Bearer YOUR_KEY" }
    }
  }
}

Works with Claude Desktop, Claude Code, Cursor and any other MCP client. No rate limits.

Related MCP server: Legal Search MCP

Quick start — self-host

The repository ships a sample corpus so a clone runs immediately:

git clone https://github.com/LimEulYoung/legal-search-mcp
cd legal-search-mcp
pip install -e .
legal-search-mcp                 # stdio
legal-search-mcp --transport http --port 8100

Register it with a client:

{
  "mcpServers": {
    "legal-search": {
      "command": "legal-search-mcp"
    }
  }
}

Configuration is all environment variables — see .env.example. Nothing is required; the defaults use the bundled corpus.

The dive tool needs a model

Four of the five tools are pure database reads. precedent_dive sends one public judgment body to a language model and asks it to extract an answer, so it needs an endpoint:

export DIVE_API_KEY=...
export DIVE_BASE_URL=https://api.openai.com/v1   # any OpenAI-compatible endpoint
export DIVE_MODEL=...

Without those three the tool is not registered and the other four run normally.

The corpus

The tools read one SQLite file. What ships here is a bounded sample, not the whole thing:

The sample is enough to exercise every tool and run the tests. For real work, use the hosted corpus.

Search combines two lexical indexes: a character-trigram FTS and a morpheme FTS built with Kiwi, fused with reciprocal rank fusion. The morpheme index is not an optimisation — Korean charge names are often two characters (사기, 절도, 폭행), and a trigram index cannot form a trigram from two characters, so those queries return nothing without it.

Judgments are non-copyrightable under Article 7 of the Korean Copyright Act. Court and case-number provenance is preserved in the data.

Building your own

scripts/build_sample_db.py carves a sample out of a full corpus and is also the reference for the schema — which tables the tools read, how the full-text indexes are built, and how statute versions resolve:

python scripts/build_sample_db.py --source /path/to/corpus.db \
    --dest my_sample.db --cases 5000 --statutes all

Paper

The retrieval and tool-use design was evaluated on the Korean Bar Examination:

Agentic RAG for Legal Question Answering in Civil Law: Evidence from the Korean Bar Examination Eul Young Lim and Jihun Park

Benchmark code, questions and per-model results are archived in legal_mcp. If you use this tool in research, please cite the paper (CITATION.cff).

Also available

• Legal Search API — one question in, a grounded answer out, in Anthropic Messages format. crow-tit.com

• 법률AI — the free consumer service: chat, search, labour calculators, legal document drafting. lawful.crow-tit.com

Notes

This is a search tool over public legal sources, not legal advice. What it returns is source material and statistics; deciding what they mean for a particular matter is a lawyer's job.

Development happens in a private repository and lands here in batches, so issues are welcome but pull requests may be merged by hand rather than through the button.

MIT licensed.