Cover image
Try Now
2025-04-12

Modelado financiero Prep Servidor MCP

3 years

Works with Finder

1

Github Watches

1

Github Forks

7

Github Stars

Financial Modeling Prep (FMP) MCP Server

A Model Context Protocol (MCP) server that provides access to Financial Modeling Prep (FMP) API data through a standardized interface. This server allows AI assistants like Claude to access financial data programmatically.

Features

  • Company Profiles: Access company information, descriptions, market caps, employee counts, and industry data
  • Financial Statements: Retrieve income statements, balance sheets, and cash flow statements
  • Financial Metrics: Get key metrics, ratios, and growth data
  • Analyst Data: Access analyst estimates and recommendations
  • SEC Filings: Find and retrieve SEC filing content
  • Earnings Transcripts: Get earnings call transcripts
  • Market Data: Access current stock prices and treasury yields
  • Competitor Analysis: Find competitor companies

Installation

Prerequisites

  • Python 3.8 or higher
  • UV package manager (recommended) or pip
  • Financial Modeling Prep API key

Setup

  1. Clone this repository

  2. Create a .env file in the project root with your API key:

    # Financial Modeling Prep API Configuration
    FMP_KEY=your_api_key_here
    
    # Optional: SEC API Configuration
    SEC_ACCESS=YourCompanyName YourEmail@example.com
    
  3. Install dependencies using UV (recommended):

    uv venv
    uv pip install -r requirements.txt
    

    Or using pip:

    pip install -r requirements.txt
    

Running the Server

Using UV (Recommended)

UV provides faster dependency resolution and installation. To run the server with UV:

# Activate the virtual environment
uv venv activate

# Run the server
python fmp_mcp_server.py

The server will start and listen for connections on the default MCP port.

Using pip

# Create and activate a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Run the server
python fmp_mcp_server.py

Connecting with Claude Desktop

Claude Desktop can connect to MCP servers to access financial data. Here's how to set it up:

  1. Download Claude Desktop
  2. Edit claude_desktop_config.json: "fmp_mcp_server": { "command": "uv", "args": [ "--directory", "REPLACE ME WITH ABSOLUTE DIRECTORY TO REPO", "run", "fmp_mcp_server.py" ] }

Now Claude can use the FMP data through the MCP interface. You can ask Claude to:

  • Get company profiles
  • Retrieve financial statements
  • Find SEC filings
  • Access market data
  • And more!

Example Queries for Claude

Once connected, you can ask Claude questions like:

  • "I am considering a 3 year horizon investment, is Apple a good investment?"
  • "Show me Tesla's latest quarterly income statement"
  • "Find the latest 10-K filing for Microsoft"
  • "What are Amazon's main competitors?"
  • "Get the latest earnings transcript for Meta"

Configuration Options

The server supports the following environment variables:

  • FMP_KEY: Your Financial Modeling Prep API key (required)
  • SEC_ACCESS: Your company name and email for SEC API access (optional)

Caching

The server implements a caching system to reduce API calls and improve performance:

  • Financial data is cached by quarter/year
  • Profile data is cached monthly
  • Daily price data is cached for the current day

Cache files are stored in the DataCache directory.

Logging

Logs are written to the logs directory with rotation enabled:

  • Maximum log file size: 10MB
  • Number of backup files: 5

License

MIT License

Acknowledgements

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

  • JackKuo666
  • 🔍 Habilitar asistentes de IA para buscar y acceder a la información del paquete PYPI a través de una interfaz MCP simple.

  • 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.

    Reviews

    4 (1)
    Avatar
    user_SD3iAXtq
    2025-04-18

    I've been using the fmp_mcp_server by shadi-fsai for a while now, and it has exceeded my expectations. The server is robust, efficient, and incredibly easy to set up. The documentation is clear, making it accessible even for those new to such applications. Highly recommend checking it out on GitHub!