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ClinicalTrials.gov MCP Server
for AI Agents

Connect your AI agent to StackOne's ClinicalTrials.gov MCP server and give it ready-to-use MCP tools out of the box. Auth, tool execution, and security all managed.

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ClinicalTrials.gov MCP Server
Built by StackOne StackOne
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Coverage

9 Agent Actions

Create, read, update, and delete across ClinicalTrials.gov — and extend your agent's capabilities with custom actions.

MCP Actions → Build Actions →

Authentication

Agent Tool Authentication

Per-user OAuth in one call. Your ClinicalTrials.gov MCP server gets session-scoped tokens with zero credentials stored on your infra.

Agent Auth →

Security

Agent Protection

Every ClinicalTrials.gov tool response scanned for prompt injection in milliseconds — 88.7% accuracy, all running on CPU.

Prompt Injection Defense →

Performance

Max Agent Context. Min Cost.

Free up to 96% of your agent's context window to enhance reasoning and reduce cost, on every ClinicalTrials.gov call.

Tools Discovery →

What is the ClinicalTrials.gov MCP Server?

A ClinicalTrials.gov MCP server lets AI agents read and write ClinicalTrials.gov data through the Model Context Protocol — Anthropic's open standard for connecting LLMs to external tools. StackOne's ClinicalTrials.gov MCP server ships with pre-built actions, fully extensible via the Connector Builder — plus managed authentication, prompt injection defense, observability, and agent execution runtime. Connect it from MCP clients like Claude Desktop, Claude Code, Cursor, Goose, and VS Code, or from agent frameworks like OpenAI Agents SDK, LangChain, and Vercel AI SDK.

All ClinicalTrials.gov MCP Tools

Every action from ClinicalTrials.gov's API, ready for your agent. Create, read, update, and delete — scoped to exactly what you need.

Studies

  • List Studies

    Search and list clinical study records

Studys

  • Get Study

    Retrieve a single clinical study by its NCT number

Studies Metadatas

  • Get Studies Metadata

    Retrieve the study data-model definition

Study Search Areas

  • List Study Search Areas

    Retrieve the search areas used by study query parameters

Study Enums

  • List Study Enums

    Retrieve all enumeration types and their allowed values

Study Sizes Stats

  • Get Study Sizes Stats

    Retrieve statistics on the byte size of study records

Field Values Stats

  • List Field Values Stats

    Retrieve value statistics for study fields

Field Sizes Stats

  • List Field Sizes Stats

    Retrieve list-size statistics for list-valued study fields

Versions

  • Get Version

    Retrieve the API version and data snapshot timestamp

Set Up Your ClinicalTrials.gov MCP Server in Minutes

One endpoint. Any framework. Your agent is talking to ClinicalTrials.gov in under 10 lines of code.

MCP Clients

Claude Desktop setup guide
Claude Code setup guide
Cursor setup guide
Goose setup guide

Agent Frameworks

Claude Desktop
{
  "mcpServers": {
    "stackone": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote@latest",
        "https://api.stackone.com/mcp?x-account-id=<account_id>",
        "--header",
        "Authorization: Basic <YOUR_BASE64_TOKEN>"
      ]
    }
  }
}

Platform Resources

MCP Code Mode: Keeping Tool Responses Out of Agent Context

Anthropic's code_execution processes data already in context. Custom MCP code mode keeps raw tool responses in a sandbox. 14K tokens vs 500.

11 min

Comparing BM25, TF-IDF, and Hybrid Search for MCP Tool Discovery

Benchmarking BM25, TF-IDF, and hybrid search for MCP tool discovery across 916 tools. The 80/20 TF-IDF/BM25 hybrid hits 21% Top-1 accuracy in under 1ms.

10 min

Indirect Prompt Injection Defense for MCP Tools: A Technical Guide

MCP tools that read emails, CRM records, and tickets are indirect prompt injection vectors. Here's how we built a two-tier defense that scans tool results in ~11ms.

12 min

MCP vs A2A: Architecture, Security, and When to Use Each

MCP vs A2A: what each protocol standardizes, how they differ, their shared security risks including indirect prompt injection, and when to use one, both, or a hybrid architecture.

12 min

MCP vs API: What 200+ Connector Builds Taught Us

MCP wraps APIs, it doesn't replace them. After building 200+ connectors that serve both, here's when each approach wins.

14 min read

ClinicalTrials.gov MCP Server FAQ

Does StackOne have a ClinicalTrials.gov MCP server?
Yes. StackOne offers a hosted ClinicalTrials.gov MCP server, and every action is tested and QA'd by StackOne. Connect it to Claude, Cursor, and any other MCP client, or to any agent framework through the AI Action SDK. It ships with managed agent authentication, prompt injection defense, and tool discovery with server-side execution that preserve your agent's context window and keep reasoning performance.
ClinicalTrials.gov MCP server vs direct API integration — what's the difference?
A ClinicalTrials.gov MCP server and direct API integration serve different use cases. Direct API integration is for software-to-software — backend code calling ClinicalTrials.gov. A ClinicalTrials.gov MCP server is for AI agents — MCP clients like Claude and Cursor, plus framework agents built with OpenAI, LangChain, or Vercel AI — discovering and calling ClinicalTrials.gov at runtime. StackOne provides both.
How does ClinicalTrials.gov authentication work for AI agents?
ClinicalTrials.gov authentication for AI agents works through a StackOne Connect Session. Create one via the dashboard or the SDK — you get an auth link and ready-to-paste config for Claude Desktop, Cursor, and other MCP clients. Your user authenticates their own ClinicalTrials.gov account; StackOne handles token exchange, storage, and refresh. Credentials never reach the LLM, and each user is isolated via origin_owner_id.
Are ClinicalTrials.gov MCP tools vulnerable to prompt injection?
Yes — ClinicalTrials.gov MCP tools can be vulnerable to indirect prompt injection. Any tool that reads user-written content — documents, messages, tickets, records, or free-text fields — is a potential vector. StackOne Defender scans every tool response before it enters the agent's context — regex patterns in ~1ms, then a MiniLM classifier in ~4ms. 88.7% accuracy, CPU-only.
What is the context bloat of a ClinicalTrials.gov agent and how do I avoid it?
Context bloat happens when ClinicalTrials.gov tool schemas and API responses eat your ClinicalTrials.gov agent's memory, preventing it from reasoning effectively. A single ClinicalTrials.gov query can return a massive JSON response, and connecting multiple tools compounds the problem. Tools Discovery and Code Mode reduce context bloat — loading only relevant tools per query and keeping raw responses out of the agent's context.
Can I limit which actions my ClinicalTrials.gov agent can access?
Yes — you can limit which actions your ClinicalTrials.gov agent can access directly from the StackOne dashboard. Toggle actions on or off, or restrict them to specific accounts, with no code changes to your agent. Session tokens can be scoped to exact actions so if one leaks, exposure stays contained.
Can I create custom agent actions for my ClinicalTrials.gov MCP server?
Yes — you can create custom agent actions for your ClinicalTrials.gov MCP server using Connector Builder. It's an integration agent your coding assistant (Claude Code, Cursor, or Copilot) can invoke to research ClinicalTrials.gov's API, generate production-ready connector YAML, test against the live API, and validate before you ship.
When should I NOT use a ClinicalTrials.gov MCP server?
Skip a ClinicalTrials.gov MCP server if your integration is purely software-to-software — direct ClinicalTrials.gov API integration is simpler when no AI agent is involved. For deterministic, compliance-critical operations (financial transactions, regulatory reporting), direct API gives you predictable behavior without agent-driven decision-making. MCP shines when AI agents need to dynamically discover and call ClinicalTrials.gov actions at runtime.
What AI frameworks and AI clients does the StackOne ClinicalTrials.gov MCP server support?
The StackOne ClinicalTrials.gov MCP server supports both. MCP clients (paste-and-go apps): Claude Desktop, Claude Code, Cursor, VS Code, Goose. Agent frameworks (code SDKs you build with): OpenAI Agents SDK, Anthropic, Vercel AI, Google ADK, CrewAI, Pydantic AI, LangChain, LangGraph, Azure AI Foundry.

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