CanLII MCP Server

CanLII MCP Server

Enables Claude Desktop to search the CanLII Canadian legal database and retrieve the full text of matching legal documents.

Category
Visit Server

README

CanLII MCP Server

A local Model Context Protocol (MCP) server for macOS that lets Claude Desktop search the CanLII Canadian legal database and read the full text of matching documents.

What it does

Exposes a single MCP tool — search_canlii — that Claude can call to:

  1. Search CanLII using either full-text or case-name search
  2. Fetch the full text of the top matching documents
  3. Return cleaned plain text (no HTML markup) back to Claude

Tool reference

search_canlii(
    query: str,
    search_type: "text" | "name" = "text",
    max_results: int = 5   # 1–10
)
search_type When to use
"text" Legal concepts, keywords, or phrases within judgment bodies
"name" Case name, document title, file number, author, or citation (e.g. R v Oakes, 2024 SCC 12)

Requirements

Installation

1. Clone the repository

git clone <repo-url>
cd canlii_mcp_server

2. Install dependencies and Chromium

uv sync
uv run playwright install chromium

3. Add the server to Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "canlii": {
      "command": "/path/to/uv",
      "args": [
        "run",
        "--project",
        "/path/to/canlii_mcp_server",
        "canlii-mcp-server"
      ]
    }
  }
}

Replace /path/to/uv with the output of which uv, and /path/to/canlii_mcp_server with the absolute path to this directory.

4. Restart Claude Desktop

Fully quit Claude Desktop (menu bar → Quit), then reopen it. The canlii server will appear under Settings → Developer.

Usage

In a Claude Desktop conversation:

"Search CanLII for cases about reasonable apprehension of bias."

"Find the case R v Oakes."

"What does CanLII say about the duty to accommodate in employment law?"

Claude will call search_canlii automatically with the appropriate search_type.

How it works

CanLII's website is a JavaScript single-page application — search results are rendered client-side and not available in raw HTML. This server uses Playwright (headless Chromium) to load pages as a real browser would, then extracts clean text with BeautifulSoup.

playwright-stealth is applied to each page load to reduce the likelihood of bot detection by CanLII's DataDome protection. Requests are rate-limited to 1.5 seconds between document fetches to avoid triggering blocks.

Note: CanLII's bot protection may occasionally flag automated requests. If Claude reports a "blocked" error, wait an hour and try again.

Development

Run unit tests

uv run pytest tests/ --ignore=tests/test_smoke.py -v

Run live integration tests (requires network access to canlii.org)

uv run pytest tests/test_smoke.py -v -s

Project structure

src/canlii_mcp_server/
    server.py   — MCP server entry point, tool registration
    search.py   — URL builder, search results parser
    fetch.py    — document text extractor, Playwright browser manager
tests/
    test_url_builder.py        — URL building (5 tests)
    test_search_parser.py      — search results parsing (4 tests)
    test_document_extractor.py — document text extraction (5 tests)
    test_smoke.py              — live integration tests (3 tests, manual)
    fixtures/                  — saved CanLII HTML used by unit tests
scripts/
    recon.py           — captures CanLII HTML structure for fixture updates
    recon_document.py  — captures a single document page slowly

Limitations

  • No full-text API: CanLII does not provide an API that returns document text — only metadata. Playwright scraping is the only viable approach.
  • Bot detection: CanLII uses DataDome. Occasional temporary blocks are possible.
  • No noteup search: CanLII's "Noteup/Discussion" search requires a document path as input rather than a free-text query. This search type is not currently supported.
  • English only: The server searches the English index (indexLang=en).

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured