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MCP-FinTechCo

by Brett777

MCP-FinTechCo Server

A production-ready Modular Command Processor (MCP) server built with FastMCP 2.0, designed for financial technology applications and data services.

Overview

MCP-FinTechCo is a scalable MCP server initially focused on providing weather data services, with plans for rapid expansion into additional financial technology tools. Built on FastMCP 2.0, it provides a robust foundation for creating and deploying AI-accessible tools and services.

Key Features

  • FastMCP 2.0 Framework: Modern, production-ready MCP implementation

  • Weather Data Tool: Real-time weather information using Open-Meteo API

  • Cloud-Ready: Designed for deployment on Google Cloud Platform

  • Extensible Architecture: Easy to add new tools and capabilities

  • Comprehensive Logging: Built-in logging for monitoring and debugging

  • Environment-Based Configuration: Flexible configuration via environment variables

Initial Tools

get_city_weather

Retrieves current weather information for any city worldwide.

Parameters:

  • city (string): Name of the city (e.g., "New York", "London", "Tokyo")

Returns:

{ "location": "San Francisco, California, United States", "latitude": 37.7749, "longitude": -122.4194, "temperature": 18.5, "temperature_fahrenheit": 65.3, "humidity": 72, "wind_speed": 15.3, "weather_code": 2, "conditions": "Partly cloudy" }

Installation

Prerequisites

  • Python 3.11 or higher

  • pip (Python package manager)

  • Git

Local Setup

  1. Clone the repository:

git clone https://github.com/YOUR-USERNAME/MCP-FinTechCo.git cd MCP-FinTechCo
  1. Create and activate a virtual environment:

Windows:

python -m venv venv venv\Scripts\activate

Linux/Mac:

python3 -m venv venv source venv/bin/activate
  1. Install dependencies:

pip install -r requirements.txt
  1. Configure environment variables:

cp .env.sample .env

Edit .env with your preferred settings (defaults work for local testing).

  1. Run the server:

python server.py

Usage

Running the Server

Local Development:

python server.py

With Custom Environment:

export LOG_LEVEL=DEBUG export MCP_SERVER_PORT=8080 python server.py

Testing the Server

Use the included test client:

python test_client.py

This will run a series of tests to validate the server's functionality.

Project Structure

MCP-FinTechCo/ ├── server.py # Main MCP server implementation ├── test_client.py # Local testing client ├── requirements.txt # Python dependencies ├── .env.sample # Environment variable template ├── .gitignore # Git ignore patterns ├── README.md # This file ├── plan.md # Project implementation plan ├── DEPLOYMENT.md # GCP deployment guide ├── startup-script.sh # VM initialization script ├── mcp-server.service # Systemd service configuration └── deploy.sh # Deployment automation script

Configuration

The server uses environment variables for configuration. See .env.sample for all available options.

Key Environment Variables

Variable

Description

Default

MCP_SERVER_NAME

Server name

mcp-fintechco-server

MCP_SERVER_VERSION

Server version

1.0.0

MCP_SERVER_PORT

Server port

8000

LOG_LEVEL

Logging level

INFO

ENVIRONMENT

Environment name

development

Development

Adding New Tools

  1. Create a new async function decorated with @mcp.tool()

  2. Add comprehensive docstring with parameters and return values

  3. Implement error handling and logging

  4. Update this README with tool documentation

  5. Add tests in test_client.py

Example:

@mcp.tool() async def your_new_tool(param: str) -> dict: """ Description of your tool. Args: param: Description of parameter Returns: Description of return value """ # Implementation here return {"result": "value"}

Testing

Run the test client to validate all tools:

python test_client.py

For specific tool testing, modify test_client.py as needed.

Deployment

See DEPLOYMENT.md for detailed instructions on deploying to Google Cloud Platform.

Quick Deployment

./deploy.sh

This script automates the deployment process to GCP.

API Documentation

Weather Codes

The server uses WMO (World Meteorological Organization) weather codes:

Code

Condition

0

Clear sky

1-3

Mainly clear to overcast

45-48

Fog

51-55

Drizzle

61-65

Rain

71-77

Snow

80-82

Rain showers

85-86

Snow showers

95-99

Thunderstorm

Troubleshooting

Common Issues

Server won't start:

  • Verify Python version: python --version (should be 3.11+)

  • Check dependencies: pip install -r requirements.txt

  • Verify .env configuration

City not found:

  • Check spelling and try different formats

  • Try including country name: "Paris, France"

  • Use official city names

API errors:

  • Check internet connection

  • Verify no firewall blocking Open-Meteo API

  • Check server logs for detailed error messages

Contributing

Contributions are welcome! Please:

  1. Fork the repository

  2. Create a feature branch

  3. Make your changes with tests

  4. Submit a pull request

Resources

License

This project is licensed under the MIT License. See LICENSE file for details.

Support

For issues, questions, or contributions:

  • Open an issue on GitHub

  • Check existing documentation

  • Review FastMCP documentation

Roadmap

Upcoming Features

  • Additional weather tools (forecasts, historical data)

  • Financial market data integration

  • Stock price lookup tools

  • Currency conversion tools

  • Economic indicator tools

  • News and sentiment analysis

  • Custom alerts and notifications

Acknowledgments


Version: 1.0.0 Last Updated: 2025-11-02

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security - not tested
F
license - not found
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quality - not tested

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Provides real-time weather data for cities worldwide using the Open-Meteo API, with planned expansion into financial technology tools including market data, stock prices, and economic indicators.

  1. Overview
    1. Key Features
  2. Initial Tools
    1. get_city_weather
  3. Installation
    1. Prerequisites
    2. Local Setup
  4. Usage
    1. Running the Server
    2. Testing the Server
  5. Project Structure
    1. Configuration
      1. Key Environment Variables
    2. Development
      1. Adding New Tools
      2. Testing
    3. Deployment
      1. Quick Deployment
    4. API Documentation
      1. Weather Codes
    5. Troubleshooting
      1. Common Issues
    6. Contributing
      1. Resources
        1. License
          1. Support
            1. Roadmap
              1. Upcoming Features
            2. Acknowledgments

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