MCP cover image
cripto-asentimiento-MCP logo
Public

cripto-asentimiento-MCP

See in Github
2025-04-14

Un servidor MCP que ofrece análisis de sentimientos de criptomonedas a los agentes de IA.

2

Github Watches

2

Github Forks

5

Github Stars

Crypto Sentiment MCP Server

An MCP server that delivers cryptocurrency sentiment analysis to AI agents, leveraging Santiment's aggregated social media and news data to track market mood and detect emerging trends.

GitHub License Python Version Status

Features

  • Sentiment Analysis: Retrieve sentiment balance (positive vs. negative) for specific cryptocurrencies.
  • Social Volume Tracking: Monitor total social media mentions and detect significant shifts (spikes or drops).
  • Social Dominance: Measure the share of discussions an asset occupies in crypto media.
  • Trending Words: Identify the most popular terms trending in cryptocurrency discussions.

Tools

Tool Name Description Parameters
get_sentiment_balance Get the average sentiment balance for an asset over a specified period. asset: str, days: int = 7
get_social_volume Fetch the total number of social media mentions for an asset. asset: str, days: int = 7
alert_social_shift Detect significant spikes or drops in social volume compared to the previous average. asset: str, threshold: float = 50.0, days: int = 7
get_trending_words Retrieve the top trending words in crypto discussions, ranked by score over a period. days: int = 7, top_n: int = 5
get_social_dominance Measure the percentage of crypto media discussions dominated by an asset. asset: str, days: int = 7

Prerequisites

  • Python: 3.10 or higher
  • Santiment API Key: Obtain a free or paid key from Santiment.

Installation

  1. Clone the Repository:

    git clone https://github.com/kukapay/crypto-sentiment-mcp.git
    cd crypto-sentiment-mcp
    
  2. Configure Client:

    {
      "mcpServers": {
        "crypto-sentiment-mcp": {
          "command": "uv",
          "args": ["--directory", "path/to/crypto-sentiment-mcp", "run", "main.py"],
          "env": {
            "SANTIMENT_API_KEY": "your_api_key_here"
          }
        }
      }
    }
    

Examples

Below are examples of natural language inputs and their corresponding outputs when interacting with the server via an MCP-compatible client:

  • Input: "What's the sentiment balance for Bitcoin over the last week?"

    • Output: "Bitcoin's sentiment balance over the past 7 days is 12.5."
  • Input: "How many times has Ethereum been mentioned on social media in the past 5 days?"

    • Output: "Ethereum's social volume over the past 5 days is 8,432 mentions."
  • Input: "Tell me if there's been a big change in Bitcoin's social volume recently, with a 30% threshold."

    • Output: "Bitcoin's social volume spiked by 75.0% in the last 24 hours, from an average of 1,000 to 1,750."
  • Input: "What are the top 3 trending words in crypto over the past 3 days?"

    • Output: "Top 3 trending words over the past 3 days: 'halving', 'bullrun', 'defi'."
  • Input: "How dominant is Ethereum in social media discussions this week?"

    • Output: "Ethereum's social dominance over the past 7 days is 18.7%."

License

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

相关推荐

  • NiKole Maxwell
  • I craft unique cereal names, stories, and ridiculously cute Cereal Baby images.

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

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

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

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

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

  • Contraband Interactive
  • Emulating Dr. Jordan B. Peterson's style in providing life advice and insights.

  • rustassistant.com
  • Your go-to expert in the Rust ecosystem, specializing in precise code interpretation, up-to-date crate version checking, and in-depth source code analysis. I offer accurate, context-aware insights for all your Rust programming questions.

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

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

  • 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

  • modelcontextprotocol
  • Servidores de protocolo de contexto modelo

  • 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.

  • huahuayu
  • Una puerta de enlace de API unificada para integrar múltiples API de explorador de blockchain similar a Esterscan con soporte de protocolo de contexto modelo (MCP) para asistentes de IA.

    Reviews

    2 (1)
    Avatar
    user_qQM7JaBZ
    2025-04-17

    I recently started using crypto-sentiment-mcp by kukapay, and I'm absolutely impressed! This tool provides insightful sentiment analysis for cryptocurrencies, guiding my investment decisions. The setup was seamless, and the data accuracy is top-notch. Highly recommended for anyone in the crypto space! For more info, check out their GitHub page: https://github.com/kukapay/crypto-sentiment-mcp.