# Model-Context-Protocol-Learning-Path

> Model-Context-Protocol-Learning-Path — swapnil3104-model-context-protocol-learning-path. Use this tool when you need to master Model Context Protocol (MCP) and integrate it into real-world applications using Python and TypeScript. It solves problems of complex MCP architecture, authentication, and security by providing a comprehensive learning path with hands-on resources and tools. With inputs including git repositories and outputs of proficient MCP implementation, use it when building MCP-based projects or seeking to enhance existing ones.

Canonical page: https://skillsregistry.net/skills/swapnil3104-model-context-protocol-learning-path  
JSON: https://api.skillsregistry.net/v1/skills/swapnil3104-model-context-protocol-learning-path

## Description

A comprehensive, hands-on learning path for mastering Model Context Protocol (MCP), covering architecture, clients, servers, tools, resources, prompts, authentication, security, and real-world integrations with Python and TypeScript.

## Trust

- **Trust score (0–1):** 0.79
- **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/swapnil3104/Model-Context-Protocol-Learning-Path)

## 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": "swapnil3104-model-context-protocol-learning-path"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/swapnil3104-model-context-protocol-learning-path` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/swapnil3104-model-context-protocol-learning-path/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