Fast LLM & Agents & MCPs

What is Fast LLM & Agents & MCPs?

This is a comprehensive educational repository covering LLM architectures, RAG, fine‑tuning, agents, MCP tools, and skills both theoretically and practically. It provides sample codes using LangChain & LangGraph (v1.0.0), AWS Strands Agents, and Google Agent Development Kit (ADK).

How to use Fast LLM & Agents & MCPs?

Clone the repository and navigate to the relevant sample directories under agents/ for each framework. No specific server configuration or invocation command is documented; users should follow the individual sample READMEs or setup instructions inside each directory.

Key features of Fast LLM & Agents & MCPs

• Covers LLM architectures, RAG, fine‑tuning, and prompt engineering.
• Provides sample agents with LangChain & LangGraph (v1.0.0).
• Provides sample agents with AWS Strands Agents.
• Provides sample agents with Google Agent Development Kit (ADK).
• Includes MCP Tool integration samples (local and remote).
• Explains concepts of agents, tools, skills, and A2A protocol.

Use cases of Fast LLM & Agents & MCPs

• Automating complex tasks like summarization, translation, and coding.
• Building intelligent chatbots, copilots, and search engines.
• Enhancing productivity with knowledge‑based task automation.
• Customizing LLMs for domain‑specific needs (finance, legal, health).
• Learning and prototyping multi‑agent workflows (sequential, parallel, hierarchy).

FAQ from Fast LLM & Agents & MCPs

What is the difference between this repository and other LLM learning resources?

This repository combines theoretical explanations with practical sample codes across three agent frameworks (LangChain/LangGraph, AWS Strands, Google ADK) and includes MCP tool integration examples.

What are the runtime requirements to run the sample codes?

The README does not explicitly list requirements, but samples use LangChain & LangGraph (v1.0.0), AWS Strands Agents, and Google ADK, which typically require Python and respective SDKs. Some samples use Streamlit for UI.

Where are the sample codes and data stored?

All sample codes and reference documents are stored within this GitHub repository under the agents/ directory, organized by framework.

Does this repository provide an MCP server to use?

No, this is a learning repository that demonstrates MCP concepts and includes sample integrations of local and remote MCP tools within agents.

What transports or authentication methods are covered?

The READ