# Model-Context-Protocol-MCP-

> Model-Context-Protocol-MCP- — hemakumar0077-model-context-protocol-mcp. Use this tool when you need to standardize communication between Large Language Models (LLMs) and external tools, data sources, and services. The Model Context Protocol (MCP) framework provides an open-source, open standard solution for integrating AI systems, solving problems of compatibility and data exchange. It takes in model inputs and outputs, and provides a standardized interface for seamless communication between LLMs and external resources.

Canonical page: https://skillsregistry.net/skills/hemakumar0077-model-context-protocol-mcp  
JSON: https://api.skillsregistry.net/v1/skills/hemakumar0077-model-context-protocol-mcp

## Description

Definitive Guide on MCP. The Model Context Protocol (MCP) is an open-source, open standard framework introduced by Anthropic on November 25, 2024. It fundamentally standardizes how artificial intelligence (AI) systems, particularly Large Language Models (LLMs), integrate and communicate with external tools, data sources, and services.

## Trust

- **Trust score (0–1):** 0.90
- **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/HemaKumar0077/Model-Context-Protocol-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": "hemakumar0077-model-context-protocol-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/hemakumar0077-model-context-protocol-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/hemakumar0077-model-context-protocol-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