# ML Experiment Tracker MCP

> Use this tool when you need to simplify tracking and querying of machine learning experiments, solving problems of complexity and accessibility in MLflow data analysis. It allows users to input plain English queries and outputs relevant experiment data, eliminating the need for dashboards or SQL knowledge. Ideal for data scientists and ML engineers seeking efficient experiment tracking and insights.

Canonical page: https://skillsregistry.net/skills/prateek-gaurav7296-experiments-mcp  
JSON: https://api.skillsregistry.net/v1/skills/prateek-gaurav7296-experiments-mcp

## Description

Query your MLflow experiments in plain English using Claude Desktop. No dashboards, no SQL — just ask.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/l6xu1lpv9q)
- **Repository:** <https://github.com/Prateek-Gaurav7296/experiments-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": "prateek-gaurav7296-experiments-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/prateek-gaurav7296-experiments-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/prateek-gaurav7296-experiments-mcp/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