OLEXI Australian Laws MCP Server

OLEXI Australian Laws MCP Server (OLEXI-MCP)

Version: 3.4 Date: 13 August 2025

OLEXI-MCP is a research project by Dr Oleksii Konashevych at the intersection of law and technology. It’s a Model Context Protocol (MCP) server that searches AustLII (www.austlii.edu.au) — the free, online database of Australian legal information (legislation and case law).

OLEXI-MCP is a free tool that lets your AI chat agent search across Australian laws. It works with any MCP-capable host, including:

• ChatGPT (via Connectors) — quick overview: https://youtu.be/WLWbtkJqq8I?si=MR8_HskYOuhUEEY0
• Claude by Anthropic
• VS Code + GitHub Copilot
• Any other MCP-supporting app
• OLEXI Chrome extension for AustLII (coming soon)

Once connected, you can ask legal questions and your AI won’t just guess — it’ll search AustLII and cite real legislation and case law, with links. In general-purpose chats (e.g., ChatGPT), you can nudge tool use by mentioning “Australian laws” or explicitly asking it to use the “OLEXI MCP” tool.

For developers and researchers:

Add manually to your own MCP host:

• The MCP tool is open source — git clone and enjoy
• Docker image is available — no hassle
• Or use the hosted endpoint: https://olexi-mcp-root-au-691931843514.australia-southeast1.run.app/

Fun’s over — boring technical stuff:

Why MCP and host-led reasoning

• Separation of concerns: the MCP server provides tools (search, URL builder) only; the host agent plans queries and writes the summary. This prevents “black-box” scraping and keeps logic inspectable.
• Portability: any MCP-capable host (VS Code, browsers, services) can orchestrate the same tools.
• Safety and least-privilege: the tool-only server holds no AI keys; the host owns AI usage and policy.

What makes AustLII different (methodology and findings) The AustLII search stack is a legacy CGI system with subtle constraints. We validated the following through careful experimentation:

• The true endpoint is the CGI script: https://www.austlii.edu.au/cgi-bin/sinosrch.cgi. “Modern” paths like /search/ return 410 and are unsuitable for programmatic queries.
• Requests must look like a real browser. At minimum include:
  • User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/138.0.0.0 Safari/537.36
  • Referer: https://www.austlii.edu.au/forms/search1.html
• Multiple database filters require repeating the key: use mask_path=… once per database; don’t comma-join.
• Parsing needs precision. Results live under div.card and each item is li.multi; naïve list scraping grabs UI tabs instead of cases.
• Database codes follow a stable taxonomy: au/[type]/[jurisdiction]/[court_code] (for example au/cases/cth/HCA, au/cases/nsw/NSWSC). See database_map.py for coverage.

Research framing: disciplined legal search, not fuzzy browsing

• Query planning enforces grouped ORs, avoids brittle date operators, and sanitises unsafe patterns before execution.
• Adaptive search modes: use method=auto for broad or vague prompts; prefer boolean (and sometimes titles-only) when scope is clear; switch modes automatically on empty previews.
• Host-side filters: optional year-from/to extraction from titles (e.g., [2024] …) and a configurable stop-list to reduce preview noise.
• Resilience: timeouts, retries, and back-off are environment-configurable; health probes are soft-gated to keep research flowing.

System architecture (high level)

MCP host → MCP tool calls → AustLII → Preview in host

• MCP server (tool-only): search_austlii, search_with_progress, build_search_url.
  • Production (Cloud Run): MCP Streamable HTTP is served at the service root path "/" (no /mcp).
  • Local: identical — serve MCP at the root path "/".
• Scraper: performs the CGI request with required headers and parses div.card > li.multi.

Endpoints

• MCP server (Streamable HTTP):
  • Production: served at the root path / (POST handshake at /).
  • Local: served at the root path /.
  • Connect a compatible host to use the tools (list_databases, search_austlii, build_search_url)

Environment variables (selected)

• AUSTLII_POLL_INTERVAL, AUSTLII_HEALTH_TIMEOUT
• AUSTLII_TIMEOUT, AUSTLII_RETRIES, AUSTLII_BACKOFF
• AUSTLII_CONNECT_TIMEOUT, AUSTLII_READ_TIMEOUT (optional, override AUSTLII_TIMEOUT for connect/read respectively)
• AUSTLII_JITTER (optional jitter proportion for retry backoff, e.g., 0.3 => ±30%)

Setup (local)

Prerequisites: Python 3.12+

See docs/how_to_start_locally.md for local start and handshake test.

MCP usage (tool-only)

• Production (recommended): point your MCP host at the Cloud Run service base URL; the MCP transport is at / (no path).
  • AU endpoint: https://olexi-mcp-root-au-691931843514.australia-southeast1.run.app/
• Local (legacy combined app): connect to /mcp if you run the host+MCP server together.
• Planning and summarisation remain in the host; this server never embeds an AI model.

AustLII mechanics (implementation notes)

• CGI endpoint: https://www.austlii.edu.au/cgi-bin/sinosrch.cgi
• Headers: strict User-Agent and Referer to mimic genuine browser traffic
• Query parameters: query, method (boolean/auto/title), meta (/au); repeat mask_path per database
• Parser: find div.card, then li.multi items; ignore sorting/navigation chrome
• URL builder: repeat mask_path keys and percent-encode parameters

Deployment

• Dockerfile and Cloud Run ready (container exposes $PORT, default 8080 in Cloud Run).
• Production region: deployed in Australia (australia-southeast1) for lower latency to Australian users and data locality.
  • Service URL (MCP at root): https://olexi-mcp-root-au-691931843514.australia-southeast1.run.app/
• See docs/deploy_cloud_run.md for build, push, and deploy steps, and suggested environment configuration.

Ethics and respectful use

• Respect AustLII’s infrastructure: moderate timeouts and retries; avoid aggressive scraping; include a real User-Agent.
• Provide clear citations and a direct results URL for verification.
• Maintain an audit trail of health checks and security events for accountability.

Acknowledgements

This project builds upon AustLII’s open access to legal materials and the MCP ecosystem for structured tool orchestration. We aim to advance practical research methods in Law & Technology while respecting the systems and communities that make such research possible.

License

MIT — see the LICENSE file for details. If you prefer a permissive license with an explicit patent grant, consider Apache-2.0.