# ClinicalTrials.gov

> Use this tool when you need to access clinical trial information, solve problems related to trial discovery and comparison, and streamline research workflows. It takes natural-language inputs and provides outputs such as study details, protocol comparisons, and recruiting site locations. Ideal for use in research contexts where efficient trial searching and analysis are required.

Canonical page: https://skillsregistry.net/skills/agents100x-clinicaltrials-gov  
JSON: https://api.skillsregistry.net/v1/skills/agents100x-clinicaltrials-gov

## Description

Provides natural-language access to ClinicalTrials.gov through 5 tools: searching trials by condition or keyword, retrieving study details, comparing protocols, accessing published results, and locating recruiting sites by geography. Connects to the public ClinicalTrials.gov API v2 without authentication. Published on PyPI as clinicaltrials-mcp, requires Python 3.12+, and runs locally via stdio transport.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** security
- **Updated:** 2026-09-01

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/agents100x-clinicaltrials-gov)
- **Repository:** <https://github.com/agents100x/clinicaltrials-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "agents100x-clinicaltrials-gov"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/agents100x-clinicaltrials-gov` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/agents100x-clinicaltrials-gov/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt