patsnap-ip-searching

Setup

Get your API key at https://open.patsnap.com

Patsnap Patent Research

This skill connects your AI agent to Patsnap's Patent Research MCP server.

Prerequisites

{
  "mcpServers": {
    "patsnap_patent_research": {
      "url": "https://connect.patsnap.com/f176d7/mcp?apikey=YOUR_API_KEY",
      "type": "streamableHttp"
    }
  }
}

For the full tool schema, refer to: https://open.patsnap.com/marketplace/mcp-servers/patsnap-ip-searching

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Instructions for AI Agents

Choose the correct workflow

• Use novelty_search for a technical solution, invention disclosure, or claim-text novelty review. Text is the primary input; images are optional supplements. Optional search channels include semantic, Boolean, paper, and web search.
• Use fto_review for invention-patent infringement-risk research based on a product or technical implementation. The required input object uses text as its primary content and can include translated text and images.
• Use design_fto for design-patent risk research. Its required input object must contain at least one image; only the first item in input.images is used, and a title is optional.
• Use a general patent-search MCP instead when the user needs open-ended discovery, query construction, or retrieval without a novelty or FTO analysis workflow.

Configure search and filters carefully

For fto_review, search.mode supports lite for rapid screening and pro for full analysis. Its search settings can also control candidate-patent count and iterative search rounds. Optional filters support country, apd, legal_status, and assignee; application-date ranges use YYYYMMDD, and assignee filters support not_in.

For design_fto, optional filters support country, apd, legal_status, and loc; loc uses Locarno classifications and application-date ranges use YYYYMMDD.

The analysis tools also accept optional execution settings for asynchronous execution or real-time progress, optional output controls such as normalized result-row limits, and an optional caller-supplied task_id.