# mcp-federated-data

> Use this tool when you need to integrate relational metadata with time-series data, solving data silo problems and enabling unified querying and analysis. It takes MySQL relational metadata and InfluxDB time-series values as inputs, outputting a unified entity layer accessible to Large Language Models (LLMs). Ideal for use cases requiring merged data insights, such as IoT monitoring, predictive analytics, or data-driven decision making.

Canonical page: https://skillsregistry.net/skills/baller-coder-mcp-federated-data  
JSON: https://api.skillsregistry.net/v1/skills/baller-coder-mcp-federated-data

## Description

Federated MCP server that joins relational metadata (MySQL) with timeseries values (InfluxDB) behind a single, LLM-friendly entity layer.

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/j20d91xksh)
- **Repository:** <https://github.com/baller-coder/mcp-federated-data>

## 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": "baller-coder-mcp-federated-data"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/baller-coder-mcp-federated-data` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/baller-coder-mcp-federated-data/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