Legal MCP — Concept & Idea

Vision

An AI-powered semantic search platform for German and European Union law, built on the Model Context Protocol (MCP). The goal is to make legal texts truly accessible — not just searchable by keyword, but queryable by meaning — for lawyers, researchers, students, and AI assistants alike.

Problem

• Legal texts are scattered across multiple official government portals (Gesetze-im-Internet, Bayern.Recht, EUR-Lex), each with different formats (XML, HTML, SPARQL endpoints).
• Traditional keyword search fails for legal research: users need to find laws by concept, not by exact wording.
• LLMs hallucinate legal citations. There is no reliable way for AI assistants to ground their answers in actual, current legal text.
• No open, standardized protocol exists for LLMs to query legal databases as tools.

Solution

1. Crawl & Ingest

Automated crawlers pull legal documents from three official sources:

• Bundesrecht — German federal law (Gesetze-im-Internet.de, XML)
• Bayern.Recht — Bavarian state law (gesetze-bayern.de, HTML)
• EUR-Lex — EU legislation (SPARQL + CELLAR endpoint)

Documents are parsed, normalized, chunked (with configurable size/overlap), and stored in PostgreSQL.

2. Semantic Embeddings

Each text chunk is embedded into a 768-dimensional vector space using Google Vertex AI (text-embedding-004). These embeddings are stored via the pgvector extension, enabling cosine-similarity search at database level.

3. Search & Retrieval

• Semantic search: Encode a natural-language query into the same vector space and find the most similar legal text chunks.
• Filtering: Narrow results by jurisdiction (federal, state, EU) and document type (law, regulation, directive, etc.).
• Related laws: Discover semantically related legislation.
• Legal changes: Track new, modified, and repealed legal texts over time.

4. RAG-Powered Legal Chat

A chat assistant powered by Gemini 2.5 Pro that:

• Automatically searches for the top relevant legal text chunks based on the user's question.
• Sends those chunks as grounded context to the LLM.
• Strictly constrains the model to only cite from provided legal texts — never from its own training data.
• Returns answers with source citations users can verify.

5. MCP Integration

Expose search capabilities via the Model Context Protocol so any MCP-compatible LLM client (e.g., Claude Desktop) can use legal search as a tool during reasoning. This turns the legal database into a first-class tool for AI assistants.

MCP Tools:

• search_laws — Semantic search across laws
• get_law_by_id — Retrieve a specific law
• search_case_law — Semantic search across court decisions
• get_legal_changes — Recent legal changes
• get_related_laws — Find related legislation

MCP Resources:

• legal://jurisdictions — Available jurisdictions
• legal://document-types — Available document types

Architecture

  Official Legal Sources              PostgreSQL + pgvector
  ┌──────────────────┐               ┌─────────────────────┐
  │ Gesetze-im-Internet │             │ laws                │
  │ Bayern.Recht       │──▶ Crawler ──▶│ law_chunks (vec768) │
  │ EUR-Lex            │   pipeline   │ case_law            │
  └──────────────────┘               │ case_law_chunks     │
                                      └─────────┬───────────┘
                                                │
                                  ┌─────────────┴─────────────┐
                                  ▼                           ▼
                          REST API (FastAPI)          MCP Server (stdio)
                          ┌───────────────┐          ┌────────────────┐
                          │ /api/search   │          │ search_laws    │
                          │ /api/chat     │          │ get_law_by_id  │
                          │ /api/laws     │          │ search_case_law│
                          │ /api/changes  │          │ ...            │
                          └───────┬───────┘          └───────┬────────┘
                                  ▼                          ▼
                          Next.js Frontend           LLM Clients
                          (Search + Chat UI)         (Claude, etc.)

Tech Stack

Layer	Technology
Crawler	Python, aiohttp, BeautifulSoup, lxml
Backend API	Python, FastAPI, SQLAlchemy 2.0 (async)
Database	PostgreSQL 15, pgvector, pg_trgm
Embeddings	Google Vertex AI text-embedding-004
LLM (Chat)	Google Vertex AI Gemini 2.5 Pro
MCP	mcp Python SDK, stdio transport
Frontend	Next.js 14, React 18, TypeScript, Tailwind, shadcn/ui
Infra	Docker Compose (dev), Cloud Run + Firebase Hosting (prod)

Monorepo Structure

packages/
  crawler/       — Legal document crawlers & processing pipeline
  mcp-server/    — FastAPI REST API + MCP protocol server
  frontend/      — Next.js web application (search + chat)
  postgres/      — Custom PostgreSQL image with pgvector

Key Design Decisions

• pgvector over dedicated vector DBs: Keeps the stack simple — one database for both relational data and vector search. Good enough for the scale of legal corpora.
• Chunking strategy: Legal texts are split into chunks with configurable size and overlap to balance retrieval precision vs. context completeness.
• Strict RAG grounding: The chat system prompt explicitly forbids the LLM from using its own knowledge, reducing hallucinated citations.
• MCP as first-class interface: Not just a REST API — the MCP protocol integration makes this a composable tool for any AI workflow.
• Rate limiting & robots.txt compliance: Crawlers respect official sources with rate limiting, retries, and robots.txt checking.

Future Directions (to refine)

• Expand to additional German state laws (currently only Bavaria)
• Add case law from court databases (Bundesgerichtshof, BVerfG, etc.)
• Support for cross-referencing between laws (citation graph)
• User accounts and saved searches
• Webhook notifications for changes in tracked laws
• HTTP-based MCP transport (currently stdio only)
• Fine-tuned embedding models for German legal language
• Multi-language support (German/English) for EU legislation

Legal Note

Official legal texts are in the public domain under German copyright law (Section 5(1) UrhG). This tool is not a substitute for professional legal advice.

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This document is a living concept note. It will be refined as the project evolves.