# Open Data Model Context Protocol

> Use this tool when you need to integrate public datasets into your application, solving data sourcing and accessibility problems. It provides access to a wide range of datasets, allowing for seamless data retrieval and utilization within LLM applications. With a simple interface, it accepts queries and returns relevant data, making it ideal for use cases requiring external data enrichment.

Canonical page: https://skillsregistry.net/skills/opendatamcp-opendatamcp  
JSON: https://api.skillsregistry.net/v1/skills/opendatamcp-opendatamcp

## Description

Access to many public datasets right from your LLM application.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-06-11

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/wxjcqeq3gt)
- **Repository:** <https://github.com/OpenDataMCP/OpenDataMCP>

## 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": "opendatamcp-opendatamcp"
    }
  }
}
```

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