# OpenDataMCP

> Use this tool when you need to integrate open data with large language models (LLMs) for enhanced analysis and insights. OpenDataMCP connects public datasets to LLMs via MCP, solving data accessibility and sharing challenges. It accepts dataset inputs and outputs connected data, ideal for use cases requiring community-driven data publishing and collaboration.

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

## Description

Connects open data to LLMs via MCP, enabling easy access to public datasets and publishing new datasets with community help.

## 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:** 2026-05-27

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/p27o08kkp6)
- **Repository:** <https://github.com/fastmcp-me/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": "fastmcp-me-opendatamcp"
    }
  }
}
```

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