How to Use the Harvard ClinicalTrials MCP in Mastra AI

Q: Does the server support batch searches for Harvard ClinicalTrials within Mastra AI?

You can loop through multiple NCT IDs using getstudy in a sequence. The server handles individual requests efficiently to avoid hitting rate limits.

Build resilient clinical research workflows in Mastra AI with automatic retries and conditional trial data handling.

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Connect Harvard ClinicalTrials MCP to Mastra AI

Create your Vinkius account to connect Harvard ClinicalTrials to Mastra AI 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 Harvard ClinicalTrials with Mastra AI

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Resilient trial data flows in Mastra AI

Create agent workflows that handle API volatility. If `get_study` fails due to a network blip, Mastra AI automatically retries the task. This ensures your clinical research pipeline stays active without manual intervention. It's built for stability in high-stakes environments.

Conditional clinical search logic

Define branching paths based on trial results. You can use `search_rare_diseases` to find a cohort, then branch to `get_study_results` if a trial is completed. Your Mastra AI agents act on the data found, not just the search query. This turns raw records into actionable trial intelligence.

Managed clinical data orchestration

Use the Harvard ClinicalTrials server to manage complex study lookups across 16 distinct tools. Everything from `search_pediatric` to `search_fda_regulated` is available to your agent. It handles the schema mapping so your workflows remain clean. You just define the agent's objective and let the server handle the API communication.

Setup guide

Set up Harvard ClinicalTrials MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Harvard ClinicalTrials tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "harvard-clinicaltrials-mcp-client",
  servers: {
    "harvard-clinicaltrials-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Harvard ClinicalTrials Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Harvard ClinicalTrials tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Harvard ClinicalTrials transactions"
);
console.log(result.text);

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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 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.

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Common questions about Harvard ClinicalTrials MCP in Mastra AI

Initialize the MCPClient in your Mastra agent configuration. Once registered, spread the tools into your agent's toolset to enable `search_studies` access.

Yes. Use the requireToolApproval setting in your Mastra configuration. This gives you a human-in-the-loop check before the agent executes a search.

The agent receives an empty response. You can configure your workflow to trigger a fallback search or notify an admin if specific data is missing.

You can loop through multiple NCT IDs using `get_study` in a sequence. The server handles individual requests efficiently to avoid hitting rate limits.

Data is transmitted over encrypted channels directly to the ClinicalTrials.gov API. The server does not log or persist any sensitive query metadata.

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