MCP server for structured intellectual property data retrieval
Project description
uyanip-mcp
MCP (Model Context Protocol) server that provides structured intellectual property data retrieval via HTTP API. Supports CN, US, EP, JP, KR, WO/PCT, and other major authorities.
Built for AI agents to seamlessly retrieve IP information during software engineering, competitive research, and analysis tasks.
Features
- Global coverage — CN / US / EP / JP / KR / WO / DE / CA / AU / GB / FR and more
- Dual number formats — application numbers and publication numbers
- Full content — bibliographic info, claims, description, drawings, PDF file download
- Auto-login — RSA-encrypted authentication via environment variables
- Session persistence — cookies and tokens survive restarts via disk cache
- Token refresh — auto-refreshes expired access tokens transparently
- Batch query — fetch multiple records with built-in rate-limit awareness
Prerequisites
- Python 3.11+
Installation
pip install uyanip-mcp
Configuration
Set the following environment variables:
| Variable | Description |
|---|---|
UYANIP_USERNAME |
Your account username (phone or email) |
UYANIP_PASSWORD |
Your account password |
Usage
With opencode
Register in opencode.jsonc:
{
"mcp": {
"uyanip-mcp": {
"type": "local",
"command": ["uvx", "uyanip-mcp"],
"environment": {
"UYANIP_USERNAME": "your-username",
"UYANIP_PASSWORD": "your-password"
}
}
}
}
Command-line
uvx uyanip-mcp
Python API
from uyanip_mcp.api_client import login_from_config, fetch_bibliographic
login_from_config()
info = fetch_bibliographic("CN115353203A")
Available Tools
| Tool | Description | Input |
|---|---|---|
login |
Authenticate with credentials | username, password |
fetch_bibliographic |
Get bibliographic information | patent_no |
fetch_claims |
Get claims text | patent_no |
fetch_description |
Get description text | patent_no |
fetch_drawings |
Get drawing image URLs | patent_no |
fetch_patent_content |
Get all content in one call | patent_no |
batch_fetch_patents |
Fetch multiple records (rate-limited) | patent_nos (array) |
fetch_patent_pdf |
Download PDF (base64-encoded) | patent_no |
License
MIT
Project details
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