# mcp-server

> mcp-server — isatyamks-mcp-server. Use this tool when you need to manage and learn from model context protocols, solving problems related to data consistency and version control in machine learning projects. It takes in git repositories as input and outputs learned model context protocols, enabling efficient collaboration and knowledge sharing. Ideal for use cases involving complex model management and deployment pipelines.

Canonical page: https://skillsregistry.net/skills/isatyamks-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/isatyamks-mcp-server

## Description

learning modelcontext protocol

## 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
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/isatyamks/mcp-server)

## 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": "isatyamks-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/isatyamks-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/isatyamks-mcp-server/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