# model-context-protocol

> model-context-protocol — syedaanif-model-context-protocol. Use this tool when you need to manage and track changes in machine learning model contexts, solving version control and collaboration problems in AI development. It provides an interface for inputs such as model configurations and outputs like versioned model states, enabling efficient model management. Use MCP in contexts where multiple stakeholders collaborate on model development, requiring transparent and reproducible model updates.

Canonical page: https://skillsregistry.net/skills/syedaanif-model-context-protocol  
JSON: https://api.skillsregistry.net/v1/skills/syedaanif-model-context-protocol

## Description

Learn about Model Context Protocol(MCP)

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/SyedAanif/model-context-protocol)

## 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": "syedaanif-model-context-protocol"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/syedaanif-model-context-protocol` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/syedaanif-model-context-protocol/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