Fast LLM Agent
This repo covers LLM, Agents, MCP Tools, Skills concepts with sample codes: LangChain & LangGraph, AWS Strands Agents, Google Agent Development Kit, Fundamentals.
What is Fast LLM Agent?
Fast LLM Agent is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to this repo covers llm, agents, mcp tools, skills concepts with sample codes: langchain & langgraph, aws strands agents, google agent development kit, fundamentals.
This repo covers LLM, Agents, MCP Tools, Skills concepts with sample codes: LangChain & LangGraph, AWS Strands Agents, Google Agent Development Kit, Fundamentals.
This server falls under the Coding Agents category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- This repo covers LLM, Agents, MCP Tools, Skills concepts wit
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx fast-llm-agent-mcpConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Fast LLM Agent
Fast LLM Agent MCP is a comprehensive educational repository and reference implementation covering LLM agents, MCP tools, and agent frameworks including LangChain, LangGraph, AWS Strands Agents, and Google Agent Development Kit (ADK). It provides working sample code and step-by-step examples for building agents with tool use, multi-agent orchestration, memory management, and MCP server integration across multiple cloud and local providers. Developers learning to build production AI agents use it as a structured curriculum covering fundamentals through advanced patterns like stateful graph workflows and fine-tuning.
Prerequisites
- Python 3.10 or later installed
- pip or uv package manager available
- API keys as needed for the frameworks you want to use: OpenAI API key for LangChain/LangGraph examples, AWS credentials for Strands Agents, or Google Cloud credentials for ADK
- Git to clone the repository
- An MCP-compatible client if testing MCP server examples
Clone the repository
Clone the Fast-LLM-Agent-MCP repository to your local machine.
git clone https://github.com/omerbsezer/Fast-LLM-Agent-MCP
cd Fast-LLM-Agent-MCPCreate a virtual environment
Create and activate a Python virtual environment to isolate dependencies.
python -m venv venv
source venv/bin/activate # macOS/Linux
# or: venv\Scripts\activate # WindowsInstall dependencies for the framework you want to explore
Each section of the repository covers a different framework. Install the relevant packages for LangChain/LangGraph, AWS Strands, or Google ADK.
# LangChain + LangGraph
pip install langchain langgraph langchain-openai
# AWS Strands Agents
pip install strands-agents
# Google Agent Development Kit
pip install google-adkSet your API credentials
Export the credentials needed for the framework examples you want to run. Different examples require different keys.
# For LangChain/LangGraph/OpenAI examples
export OPENAI_API_KEY=sk-your-openai-key
# For AWS Strands
export AWS_ACCESS_KEY_ID=your-key-id
export AWS_SECRET_ACCESS_KEY=your-secret
export AWS_DEFAULT_REGION=us-east-1Run the sample scripts
Navigate to the relevant section and run the example scripts. Each folder contains standalone samples demonstrating a specific pattern.
# Example: run a LangGraph agent sample
python langraph/basic_agent.pyExplore the MCP tool examples
The repository includes MCP server and tool integration samples showing how to connect agents to external data sources using the Model Context Protocol.
Fast LLM Agent Examples
Client configuration
If using the MCP server sample from the repository with Claude Desktop, configure it as a local Python server.
{
"mcpServers": {
"fast-llm-agent-mcp": {
"command": "python",
"args": ["/absolute/path/to/Fast-LLM-Agent-MCP/mcp_server/server.py"],
"env": {
"OPENAI_API_KEY": "sk-your-openai-key"
}
}
}
}Prompts to try
Use these prompts when exploring the agent framework samples and MCP tool integration examples.
- "Show me how to create a LangGraph agent with tool use and state management"
- "What is the capital city of France?" (tests basic tool invocation example)
- "Explain the difference between LangGraph and AWS Strands Agents for multi-agent workflows"
- "Walk me through building an MCP server that exposes a Python function as a tool"Troubleshooting Fast LLM Agent
ImportError when running a framework sample
Each framework section may have different dependencies. Check the requirements.txt or README in the specific subfolder and install only the packages for that section. Avoid installing all frameworks at once to prevent dependency conflicts.
API key errors when running LangChain or LangGraph examples
Ensure OPENAI_API_KEY is exported in the same terminal session where you run the script, or add it to a .env file in the project root if the sample uses python-dotenv to load environment variables.
AWS credentials not found for Strands Agents examples
Configure AWS credentials using 'aws configure' or by setting AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, and AWS_DEFAULT_REGION environment variables. Ensure your IAM user or role has permission to invoke the Bedrock models used in the examples.
Frequently Asked Questions about Fast LLM Agent
What is Fast LLM Agent?
Fast LLM Agent is a Model Context Protocol (MCP) server that this repo covers llm, agents, mcp tools, skills concepts with sample codes: langchain & langgraph, aws strands agents, google agent development kit, fundamentals. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Fast LLM Agent?
Follow the installation instructions on the Fast LLM Agent GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Fast LLM Agent?
Fast LLM Agent works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Fast LLM Agent free to use?
Yes, Fast LLM Agent is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
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Browse More Coding Agents MCP Servers
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Set Up Fast LLM Agent in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
Ready to use Fast LLM Agent?
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