deeparchi-patent-mcp 1.4.1

MCP Server for global patent data retrieval and analysis

Patent MCP Server

🚀 Clone. Install. Done. Give your AI agent the ability to read global patents — no API key, no cloud, no external service.

An MCP (Model Context Protocol) server that gives AI agents access to global patent data — 1.4 billion patent records, Chinese full-text included. Runs locally on your machine. No external API, no subscription.

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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.

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30-Second Install

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

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Quick Start

Pick your agent platform and add this to its MCP config:

Claude Desktop

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

Cursor / Windsurf / Cline

Same config as Claude Desktop above.

Hermes Agent

mcp_servers:
  patent-mcp:
    command: "python"
    args: ["-m", "src.server"]
    workdir: "/path/to/patent-mcp-server"

Any MCP Client (via mcp.json)

mcp-get install deeparchi-ai/patent-mcp-server

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Now ask your agent:

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

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What's Included

Tool	What It Does	Needs Setup?
get_patent	Full patent details: classifications, citations (X/Y/A/D), inventors, assignees, family	No
get_patent_claims	US patent claims text — the legal scope of protection	No
search_patents	Search 1.4B patents by keyword, country, CPC, date range	Optional GCP

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

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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:

   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:

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

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

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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.

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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.

get_patent_claims

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

Returns: full claims text. (US patents only; non-US return empty.)

search_patents

search_patents(query="transformer attention", country="CN", after="2023-01-01", limit=5)

CN results include Chinese titles and abstracts. At least one of country, cpc, or after is required.

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How It Works

┌──────────────┐     ┌─────────────────────────────┐
│  AI Agent    │────▶│  patent-mcp-server          │
│  (Claude,    │     │  (runs on YOUR machine)     │
│   Cursor,    │     │                             │
│   Hermes)    │     │  ┌──────────┐ ┌───────────┐ │
│              │     │  │ Web      │ │ BigQuery  │ │
│              │     │  │ Scraper  │ │ Client    │ │
│              │     │  │ (free)   │ │ (optional)│ │
│              │     │  └────┬─────┘ └─────┬─────┘ │
│              │     │       │             │       │
│              │     │  Google Patents   BigQuery  │
│              │     │  Public Pages     1.4B rows │
└──────────────┘     └─────────────────────────────┘

• Web scraping for details — fast (~1.5s), free, no credentials
• BigQuery for search — 1.4B records, CN full-text, optional
• Smart fallback — get_patent tries web first, auto-falls to BigQuery if you have it

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Development

pip install -e ".[dev]"

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

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License

MIT — see LICENSE.

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Author

DeepArchi OPC — AI agent infrastructure for enterprise architecture.