How to Use the USPTO API MCP in LangChain

Q: If I run into an API issue, how does USPTO API help me using LangChain?

You start the process by calling checkapistatus. This ensures your entire chain doesn't break because of a temporary service outage. It’s always best practice to check status first.

Q: Can I use USPTO API with LangChain to get all classification codes?

Absolutely. The listpatentclasses tool provides the complete list of patent classification codes, giving you a full map of how US patents are categorized.

Build multi-step IP audits and complex reasoning chains with LangChain.

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Connect USPTO API MCP to LangChain

Create your Vinkius account to connect USPTO API to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup USPTO API with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Deep Dive Patent Analysis

Start by running `search_patents` to find US patents matching specific keywords. You'll get a list of relevant patent numbers, which you can immediately pipe into the `get_patent_details` tool. This sequence allows your agent to gather full documentation for every potential hit found during the initial search.

Trademark Verification Chains

Need to vet a brand name? Use `search_trademarks` first; it pulls up all existing US trademarks related to your keyword. Next, call `get_trademark_details` for specific serial numbers to confirm status and ownership history. This two-step process builds reliable IP verification chains.

API Health Check & Classification Mapping

Before starting a big audit, you should always check the system health using `check_api_status`. If that's good to go, next call `list_patent_classes` to get all available patent classification codes. This lets your agent understand the entire scope of US intellectual property categorization.

Setup guide

Set up USPTO API MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes USPTO API tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "uspto-api-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent USPTO API transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by USPTO API. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about USPTO API MCP in LangChain

You construct a multi-step chain where one tool's output feeds directly into the next. For example, you search patents using `search_patents`, and then pass those results to `get_patent_details` to pull all the granular data needed.

Yes. Because LangChain supports complex agent pipelines, you can build an agent that decides whether it needs to check patents or trademarks, and executes both tool sets in the correct order for a full audit.

This server handles two main types of intellectual property: detailed patent records (from `get_patent_details`) and comprehensive trademark details (from `get_trademark_details`). The agent can work with both.

You start the process by calling `check_api_status`. This ensures your entire chain doesn't break because of a temporary service outage. It’s always best practice to check status first.

Absolutely. The `list_patent_classes` tool provides the complete list of patent classification codes, giving you a full map of how US patents are categorized.

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