# mcp-model-orchestrator

> mcp-model-orchestrator — ahmedkurov-mcp-model-orchestrator. Use this tool when you need to manage and deploy multiple machine learning models, such as summarization, sentiment analysis, and keyword extraction, via a REST API. It solves problems of model versioning and tracking by utilizing Git, allowing for seamless improvements and updates. The mcp-model-orchestrator takes in model inputs and returns analysis outputs, making it ideal for applications requiring automated text analysis and version control.

Canonical page: https://skillsregistry.net/skills/ahmedkurov-mcp-model-orchestrator  
JSON: https://api.skillsregistry.net/v1/skills/ahmedkurov-mcp-model-orchestrator

## Description

A Python app that uses a Model Control Plane (MCP) to orchestrate three simple ML models (summarization, sentiment analysis, keyword extraction) via a REST API. All model versions and improvements are tracked with Git.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** Apache-2.0
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/ahmedkurov/mcp-model-orchestrator)

## 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": "ahmedkurov-mcp-model-orchestrator"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ahmedkurov-mcp-model-orchestrator` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ahmedkurov-mcp-model-orchestrator/pull`

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