How to Use the ClinicalTrials.gov MCP in LangChain

Build ReAct agents in LangChain that query live clinical trial registries and chain the results directly into your custom reasoning pipelines.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect ClinicalTrials.gov MCP to LangChain

Create your Vinkius account to connect ClinicalTrials.gov 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.

GDPR Free for Subscribers

Setup ClinicalTrials.gov with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain trial searches in LangChain

Your agent needs to locate experimental therapies before it can analyze them. Using `search_clinical_trials`, the pipeline pulls active studies based on sponsor or drug name. The output immediately feeds into the next node of your LangGraph setup. You don't write glue code to parse the registry responses.

Deep dive into NCT identifiers

Sometimes a broad search returns hundreds of hits, but your chain only cares about one specific study. The `get_trial_details` tool grabs the exact protocol, phase, and sponsor data using the NCT ID. This means your agent can run a map-reduce operation over a list of IDs. It fetches the full text for each trial and summarizes the inclusion criteria in parallel.

Match patients to open enrollments via MCP Server

Finding active studies takes too long when you scrape web pages. The `find_recruiting_trials` tool gives your agent direct access to structured enrollment data for any medical condition. You can route this data straight into a vector store or a prompt template. The MCP protocol handles the connection, so your focus stays on building the actual agent logic.

Setup guide

Set up ClinicalTrials.gov 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 ClinicalTrials.gov 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({
    "clinicaltrialsgov-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 ClinicalTrials.gov transactions"
    })
    print(result["messages"][-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by ClinicalTrials.gov. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect ClinicalTrials.gov now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about ClinicalTrials.gov MCP in LangChain

Install the langchain-mcp-adapters package and pass your Vinkius endpoint to MultiServerMCPClient. Then call client.get_tools() and hand them to your ReAct agent.

Yes, the search tool supports phase and recruitment status filters. Your agent can specify Phase 3 when it builds the query.

Writing custom parsers for the registry's complex JSON is a waste of time. This server provides clean, agent-ready schemas that plug right into your chains.

Every request to the registry shows up in your LangSmith traces. You see the exact search parameters the agent used and the latency of the response.

Vinkius runs this integration in an ephemeral V8 Isolate Sandbox. When your agent passes medical condition keywords or geographic filters, the sandbox vanishes after execution, leaving zero residual data behind.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript