An MCP server for AI-assisted prior-art patent search. Ask about an idea in plain English, or point it at your own codebase to find patent-worthy mechanisms you didn't even think to search for.
Describe an idea in plain English to Claude, Cursor, or any MCP-compatible AI client. Patlas searches real USPTO/EPO patent data and has your AI reason over the actual claims text — ranked matches, not a guess.
Connect Patlas to a codebase-aware AI agent (Claude Code, via the free
patent-scan Skill) and it reads through your product's own source code to surface
specific mechanisms and features worth checking — things you built but never thought to search for —
then runs each one through real patent search automatically.
Your code itself never reaches Patlas or leaves your machine: the agent reads it locally and only sends short, plain-English descriptions of each mechanism to search.
Once a codebase scan finds something worth a closer look, ask your assistant to package the findings into a formatted "Patent Landscape & Prior-Art Audit" — a one-time $299 purchase that generates a permanent, hosted report page (with print-friendly formatting) you can hand to an attorney or investor, instead of just a chat transcript. Every cited patent is independently re-verified before it appears in the report.
One flat $199/month bill covers up to 8 seats (100 calls/seat/month) — every team member signs in with their own GitHub identity, no shared credentials. Ask your assistant to "create a team called Acme Corp" to get started; anyone can start one regardless of their own current tier.
Watch a technology area for new filings — Patlas checks once a day and posts to a webhook you supply when something new matching your query shows up. Available on Pay-as-you-go, Subscription, and Team (up to 5 watches per account).
A plain REST API (not MCP-specific) for approved integration partners white-labeling patent search under their own brand — admin-assigned, metered per call. Not self-serve: contact us to discuss an integration.
The risk with AI-generated patent analysis is hallucination — an LLM confidently inventing a patent ID or a claim quote that doesn't actually exist. Patlas validates every similarity claim and every quoted claim-language snippet against the real, retrieved patent text before it's returned. If a claim can't be grounded in the actual source document, it's dropped or corrected — not surfaced to you as fact. This is enforced in code, not just prompted. It reduces hallucination risk; it doesn't make the analysis complete or a substitute for professional review — see the disclaimer below.
search_prior_art, get_patent_detail, or compare_claims — processed to generate the AI analysis, and used to query USPTO/EPO for patent data.patent-scan against your own codebase: only the short, plain-English description of each mechanism your AI agent writes after reading your code — not the code itself. Generating a paid report from a scan sends that same mechanism/summary text plus the patent IDs you're citing — never your code — so the report can verify each citation and render the document.patent-scan, your AI agent reads it locally; the code itself never reaches Patlas or whatever powers the analysis behind it.Full detail in our Privacy Policy, including exactly which providers your data is sent to and why.
| Tier | Price | What you get |
|---|---|---|
| Free | $0 | 2 calls/month — search_prior_art + get_patent_detail |
| Pay-as-you-go | $3/call | Unlimited calls, all tools including compare_claims and landscape_summary |
| Subscription | $49/month | 20 calls/month, all tools |
| Team | $199/month | Up to 8 seats, 100 calls/seat/month, all tools shared across the team |
| Landscape & Prior-Art Audit report | $299 one-time | A permanent, shareable report from a codebase scan — not a subscription, buy one whenever you need it |
No seats requirement, no annual contract, no sales call — Team's 8 seats are a cap, not a minimum.
Sign in with GitHub — no separate signup, no API key to manage or lose.
Don't have Claude Code, Claude Desktop, or Cursor set up? Use Patlas directly in your browser — same tools, same account, no MCP client required.
.mcp.json){
"mcpServers": {
"patlas": {
"type": "http",
"url": "https://patlas.dev/mcp"
}
}
}{
"mcpServers": {
"patlas": {
"command": "npx",
"args": ["mcp-remote", "https://patlas.dev/mcp"]
}
}
}Restart your AI client — a browser window will prompt you to sign in with GitHub on first use.