# EOSC Data Commons Search

> Use this tool when you need to discover and access open-access scientific datasets using natural language search. It solves problems of data discovery and retrieval by providing tools to search and retrieve file metadata through the EOSC Data Commons OpenSearch service. The tool accepts natural language queries as input and returns relevant dataset metadata as output, ideal for researchers and scientists seeking specific data for their studies.

Canonical page: https://skillsregistry.net/skills/eosc-data-commons-data-commons-search  
JSON: https://api.skillsregistry.net/v1/skills/eosc-data-commons-data-commons-search

## Description

Enables natural language search and discovery of open-access scientific datasets through the EOSC Data Commons OpenSearch service. Provides tools to search datasets and retrieve file metadata using LLM-assisted queries.

## Trust

- **Trust score (0–1):** 0.42
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/bh1ub4y2jv)
- **Repository:** <https://github.com/EOSC-Data-Commons/data-commons-search>

## 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": "eosc-data-commons-data-commons-search"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/eosc-data-commons-data-commons-search` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/eosc-data-commons-data-commons-search/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