Cover image
Try Now
2025-04-07

Flex MCP Agent es un agente con AI diseñado para interactuar con los servidores MCP para procesar y resolver consultas de usuarios. Simplemente configúrelo con los servidores MCP y mire lo escalar sin esfuerzo, sin límites, sin cuellos de botella.

3 years

Works with Finder

1

Github Watches

0

Github Forks

0

Github Stars

Flex MCP Agent

Agent that integrates weather data retrieval, Confluence interaction and email sending functionalities. It uses a structured chat agent to interact with users and perform tasks based on user input. The project leverages the Model Context Protocol (MCP) to standardize interactions between the agent and various data sources.

Model Context Protocol (MCP)

The Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to large language models (LLMs). It acts like a USB-C port for AI applications, providing a standardized way to connect AI models to various data sources and tools. This protocol enables secure, two-way connections between data sources and AI-powered tools, facilitating seamless integration and interaction.

Project Structure

  • mcp_weather_server.py: A server that provides weather data using the Open-Meteo API.
  • mcp_email_server.py: A server that sends emails using the SendGrid API.
  • mcp_agent.py: The main agent script that initializes the agent, loads configurations, and handles user input.
  • prompt.py: Contains the system prompt for the agent, guiding its behavior and responses.
  • config.example.json: An example configuration file for setting up server URLs and transports.
  • requirements.txt: Lists the Python dependencies required for the project.
  • .env.example: An example environment file for setting up necessary environment variables.

Setup Instructions

  1. Clone the Repository

    git clone git@github.com:MahithChigurupati/Flex-MCP-Agent.git
    cd Flex-MCP-Agent
    
  2. Create a Virtual Environment

    python3 -m venv .venv
    source .venv/bin/activate
    
  3. Install Dependencies

    pip install -r requirements.txt
    
  4. Configuration

    • Copy config.example.json to config.json and update the URLs and transport methods as needed.
    • Copy .env.example to .env and fill in the required environment variables, such as SENDGRID_API_KEY and FROM_EMAIL.
  5. Running the Servers

    • Start the weather server:

      python mcp_weather_server.py
      
    • Start the email server:

      python mcp_email_server.py
      
    • For the Confluence MCP server, please check my other Git repository to clone and set it up.

  6. Running the Agent

    python mcp_agent.py
    

Usage

  • Weather Data: The agent can fetch current weather data for specified coordinates.
  • Email Sending: The agent can send emails using the SendGrid service.
  • Confluence Integration: The agent can interact with Confluence using available tools.

Environment Variables

  • SENDGRID_API_KEY: API key for SendGrid.
  • FROM_EMAIL: The email address from which emails will be sent.
  • OPENAI_MODEL: The model name for OpenAI's language model.

Dependencies

The project requires the following Python packages:

  • langchain_mcp_adapters
  • langchain_openai
  • langchain
  • python-dotenv
  • sendgrid

相关推荐

  • Joshua Armstrong
  • Confidential guide on numerology and astrology, based of GG33 Public information

  • https://suefel.com
  • Latest advice and best practices for custom GPT development.

  • Emmet Halm
  • Converts Figma frames into front-end code for various mobile frameworks.

  • Elijah Ng Shi Yi
  • Advanced software engineer GPT that excels through nailing the basics.

  • https://maiplestudio.com
  • Find Exhibitors, Speakers and more

  • lumpenspace
  • Take an adjectivised noun, and create images making it progressively more adjective!

  • https://appia.in
  • Siri Shortcut Finder – your go-to place for discovering amazing Siri Shortcuts with ease

  • Carlos Ferrin
  • Encuentra películas y series en plataformas de streaming.

  • Yusuf Emre Yeşilyurt
  • I find academic articles and books for research and literature reviews.

  • tomoyoshi hirata
  • Sony α7IIIマニュアルアシスタント

  • apappascs
  • Descubra la colección más completa y actualizada de servidores MCP en el mercado. Este repositorio sirve como un centro centralizado, que ofrece un extenso catálogo de servidores MCP de código abierto y propietarios, completos con características, enlaces de documentación y colaboradores.

  • ShrimpingIt
  • Manipulación basada en Micrypthon I2C del expansor GPIO de la serie MCP, derivada de AdaFruit_MCP230xx

  • jae-jae
  • Servidor MCP para obtener contenido de la página web con el navegador sin cabeza de dramaturgo.

  • ravitemer
  • Un poderoso complemento Neovim para administrar servidores MCP (protocolo de contexto del modelo)

  • patruff
  • Puente entre los servidores Ollama y MCP, lo que permite a LLM locales utilizar herramientas de protocolo de contexto del modelo

  • pontusab
  • La comunidad de cursor y windsurf, encontrar reglas y MCP

  • av
  • Ejecute sin esfuerzo LLM Backends, API, frontends y servicios con un solo comando.

  • WangRongsheng
  • 🧑‍🚀 全世界最好的 llM 资料总结(数据处理、模型训练、模型部署、 O1 模型、 MCP 、小语言模型、视觉语言模型) | Resumen de los mejores recursos del mundo.

  • Mintplex-Labs
  • La aplicación AI de escritorio todo en uno y Docker con trapo incorporado, agentes de IA, creador de agentes sin código, compatibilidad de MCP y más.

  • modelcontextprotocol
  • Servidores de protocolo de contexto modelo

    Reviews

    4 (1)
    Avatar
    user_kTz7Vag8
    2025-04-17

    I've been using Flex-MCP-Agent for a while now and it's absolutely fantastic! Developed by MahithChigurupati, this tool integrates seamlessly into my workflow, offering robust performance and versatility. The interface is intuitive and the functionalities are comprehensive, making it an indispensable asset for any MCP application enthusiast. You can check it out yourself at https://github.com/MahithChigurupati/Flex-MCP-Agent. Highly recommended!