This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python.
By leveraging Python SDK / OpenAI API, the application isolates runtime dependencies while maintaining low-latency execution traces across multi-step LLM operations.
High-throughput parsing of complex documents (PDFs, Word docs, spreadsheets, presentations)
Structured table, key-value, and metadata extraction directly into agent memory buffers
Automated report generation and document synthesis from multi-source repositories
{
"mcpServers": {
"for-beginners": {
"command": "python",
"args": [
"-m",
"for_beginners"
]
}
}
}
Paste into your client configuration file (e.g. ~/Library/Application Support/Claude/claude_desktop_config.json on macOS or %APPDATA%/Claude/claude_desktop_config.json on Windows).
Clone microsoft/mcp-for-beginners from GitHub
Install dependencies with pip install -r requirements.txt (or uv sync)
Copy .env.example to .env and add your API keys
Run the skill server and connect your AI client via stdio or HTTP
Keeps heavy parsing and raw file structures external to the LLM. Only sanitized excerpts and structured returns are injected into agent memory turns.
Enforce explicit directory allowlists and permission scopes in client configuration to ensure autonomous tool calls never breach system boundaries.
Executes in an isolated local child process communicating strictly over JSON-RPC via stdio with explicit process timeouts.
Mcp For Beginners is an open-source document capability designed for AI clients and autonomous agents. This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python.
Follow the step-by-step installation: 1) Verify your runtime (Python 3.10+), 2) Add the configuration snippet into your AI client settings (e.g. claude_desktop_config.json), 3) Restart the client to initialize tool execution.
Mcp For Beginners is compatible with all AI tools supporting tool-calling and the Model Context Protocol (MCP), including Claude Desktop, Cursor, Claude Code CLI, Windsurf, OpenCode, and custom agent runtimes.
Mcp For Beginners executes locally with strict directory allowlists and permission scopes. Heavy parsing and raw file structures stay external to the LLM context window to prevent memory saturation and unauthorized access.
Yes, Mcp For Beginners is published under the MIT open-source license. You can inspect the source code and contribute on GitHub at https://github.com/microsoft/mcp-for-beginners.
Explore open-source implementation code, license, and community releases.
Anthropic's official Claude Skills for working with document formats — fill, merge, and extract data from PDFs, Word files, PowerPoint decks, and Excel spreadsheets inside agent workflows.
Reverse engineer anything with agents, from app behavior down to native binaries.
The AI SEO Audit Team is an autonomous, multi-agent workflow built with Google ADK. It takes a webpage URL, crawls the live page, researches real-time SERP competition, and produces a polished, prioritized SEO optimization report.
RAG Tutorials & PipelinesA privacy-focused legal analysis team powered by local Ollama models, Agno, and Qdrant vector search to analyze contracts and legal documents offline.
MCP AI AgentsThis example demonstrates how to connect an ADK agent to a filesystem MCP server using the MCPToolset. The agent can perform file operations like reading, writing, and listing files through the Model Context Protocol.