Google Patents (SerpAPI)▌

by kunihiros
Search Google Patents with SerpAPI. Access the Google patent website to find patents and search trade marks quickly and
Search Google Patents using the SerpAPI.
best for
- / Patent researchers and IP lawyers
- / R&D teams doing prior art searches
- / Inventors checking existing patents
- / Academic researchers studying innovations
capabilities
- / Search Google Patents by keywords
- / Retrieve patent titles and descriptions
- / Access inventor information
- / Get patent filing and publication dates
- / Query patent classification data
what it does
Search Google Patents database using the SerpAPI service. Returns patent information including titles, descriptions, inventors, and filing details.
about
Google Patents (SerpAPI) is a community-built MCP server published by kunihiros that provides AI assistants with tools and capabilities via the Model Context Protocol. Search Google Patents with SerpAPI. Access the Google patent website to find patents and search trade marks quickly and It is categorized under search web.
how to install
You can install Google Patents (SerpAPI) in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Google Patents (SerpAPI) is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
README content is unavailable from source data for this server.
Open GitHub repositoryFAQ
- What is the Google Patents (SerpAPI) MCP server?
- Google Patents (SerpAPI) is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Google Patents (SerpAPI)?
- This profile displays 29 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Ratings
4.5★★★★★29 reviews- ★★★★★Pratham Ware· Dec 12, 2024
Google Patents (SerpAPI) has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Zaid Taylor· Sep 25, 2024
I recommend Google Patents (SerpAPI) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★James Abebe· Sep 9, 2024
Google Patents (SerpAPI) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Yash Thakker· Sep 1, 2024
We evaluated Google Patents (SerpAPI) against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Benjamin Abbas· Aug 28, 2024
Google Patents (SerpAPI) is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Dhruvi Jain· Aug 20, 2024
Useful MCP listing: Google Patents (SerpAPI) is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Lucas Jackson· Aug 16, 2024
Google Patents (SerpAPI) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Yuki Gupta· Jul 27, 2024
Google Patents (SerpAPI) has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Kaira Brown· Jul 19, 2024
According to our notes, Google Patents (SerpAPI) benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Oshnikdeep· Jul 11, 2024
Google Patents (SerpAPI) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
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