Patent MCP Server

🚀 中国专利最准确的开源 MCP。 Give your AI agent the ability to read CN patents with real accuracy — plus global coverage.

An MCP (Model Context Protocol) server that gives AI agents access to patent data — CN patents with CPC-aware correction, plus US/WO global coverage. Runs locally on your machine. No external API, no subscription. Always MIT.

Why Self-Deployed

• It's just Python. Install it, your agent uses it. No server to maintain, no credential to share.
• No API key for 80% of use cases. Patent details and claims come straight from Google Patents public pages.
• Your data stays local. Nothing leaves your machine except the same HTTP requests a browser would make.
• BigQuery search is optional. Only turn it on if you need full-text search across 1.4B records.

30-Second Install

pip install deeparchi-patent-mcp

Or from source:

git clone https://github.com/deeparchi-ai/patent-mcp-server.git
cd patent-mcp-server
pip install -e .

Quick Start

After pip install, the deeparchi-patent-mcp console script is on your PATH. Add this to your agent platform's MCP config:

Claude Desktop

{
  "mcpServers": {
    "patent-mcp": {
      "command": "deeparchi-patent-mcp",
      "args": []
    }
  }
}

Cursor / Windsurf / Cline

Same config as Claude Desktop above.

Hermes Agent

mcp_servers:
  patent-mcp:
    command: "deeparchi-patent-mcp"

BigQuery is optional. Without GCP_PROJECT_ID the server starts normally and the web-backed tools work with no credentials. BigQuery-backed tools return a message explaining how to enable them. To turn them on, add an env var:

config.json

Copy

{
  "mcpServers": {
    "patent-mcp": {
      "command": "deeparchi-patent-mcp",
      "args": [],
      "env": { "GCP_PROJECT_ID": "your-gcp-project" }
    }
  }
}

Running from a source checkout

{
  "mcpServers": {
    "patent-mcp": {
      "command": "python",
      "args": ["-m", "server"],
      "cwd": "/path/to/patent-mcp-server/src"
    }
  }
}

Now ask your agent:

"Get patent US-7650331-B1 and summarize the claims."

What's Included

The first two cover 80% of use cases. Zero cost. Zero setup.

CN Patent Search (v1.7.0)

Three-layer discovery for Chinese patents:

• Keyword search works: query="芯片" + country=CN searches both English AND Chinese abstracts (v1.5.2 fix).
• Assignee filter: assignee="BOE" + country=CN → company/city-level patent landscape.
• CPC classification: Use parent CPC classes (H01L) for broader CN coverage; specific CPC codes (H01L25/065) trigger web fallback.
• See SEARCH_GUIDE.md for detailed search strategy and tested CPC codes.

Optional: Enable BigQuery Search

If you need search_patents, add a GCP project:

1. Create a GCP project with BigQuery enabled
2. Create a service account, download JSON key
3. Set env vars:
   server.ts

   Copy

   export GOOGLE_APPLICATION_CREDENTIALS="/path/to/key.json"
   export GCP_PROJECT_ID="your-project-id"
   

4. Copy the wrapper template and fill in your paths:
   bash

   Copy

   cp run.sh.example run.sh
   # Edit run.sh → set your GCP paths
   

BigQuery free tier: 1 TB/month — individual use is essentially free.

Advanced: Team Server (HTTP/SSE)

Need multiple people to share one patent-mcp instance? Start it as an HTTP server:

cp run-http.sh.example run-http.sh
# Edit → set GCP creds (skip if only using web tools)
PORT=8090 ./run-http.sh

Team members connect with:

mcp_servers:
  patent-mcp:
    url: "http://<server-ip>:8090/sse"

A systemd service template is included for production deployment.

How It Works

┌──────────────┐     ┌───────────────────────────────────────┐
│  AI Agent    │────▶│  patent-mcp-server                    │
│  (Claude,    │     │  (runs on YOUR machine)               │
│   Cursor,    │     │                                       │
│   Hermes)    │     │  search_patents:                      │
│              │     │    ┌──────────┐    ┌───────────────┐  │
│              │     │    │ BigQuery │───▶│ Firecrawl     │  │
│              │     │    │ (primary)│    │ (CN fallback) │  │
│              │     │    └──────────┘    └───────┬───────┘  │
│              │     │                           │           │
│              │     │  get_patent / get_patent_claims:      │
│              │     │    ┌──────────────────────┐           │
│              │     │    │ Google Patents (web) │           │
│              │     │    │ → BigQuery fallback  │           │
│              │     │    └──────────────────────┘           │
└──────────────┘     └───────────────────────────────────────┘

• Web scraping for details — fast (~1.5s), free, no credentials
• BigQuery for search — 1.4B records, CN full-text, optional
• Firecrawl for CN fallback — kicks in when BigQuery cost-rejects specific CPC queries
• Smart fallback — every tool tries web first, auto-falls to BigQuery if you have it

Tools Reference

get_patent

get_patent(publication_number="US-7650331-B1")

Returns: classifications, citations (X/Y/A/D prior art markers), family ID, dates, inventors, assignees. Cites prior art markers so your agent can assess novelty at a glance.

CN patent note: Google Patents web scraping provides machine-translated English data for CN patents. CPC codes from web scraping are empty (JS-rendered). For CPC, use BigQuery path.

get_patent_claims

get_patent_claims(publication_number="US-7650331-B1")

Returns: full claims text. Supports US, CN (machine-translated English), and most countries via Google Patents web scraping.

search_patents

search_patents(cpc="G06N", country="CN", after="2023-01-01", limit=5)
search_patents(assignee="TSMC", country="CN")
search_patents(query="芯片", country="CN")          # keyword search (CN: searches both EN+ZH)

Search 1.4B patents by keyword, CPC classification, assignee, country, date range. For CN patents, keyword search scans both English and Chinese abstracts.

Cost control: Queries require at least one filter (cpc/country/assignee/after). A dry-run budget guard rejects queries over 50 GB. When BigQuery rejects a CN CPC query (e.g., H01L25/065 → 256 GB), the web fallback automatically searches via Firecrawl.

See SEARCH_GUIDE.md for best practices and docs/cn-cpc-correction-table.md for tested CPC codes.

Development

pip install -e ".[dev]"

pytest tests/ -v          # 32 tests, ~1.5s
ruff check src/ tests/    # lint
mypy src/                 # type check

License

MIT — see LICENSE.

Author

DeepArchi OPC — AI agent infrastructure for enterprise architecture.