MCP cover image
See in Github
2025-04-14

向AI代理提供加密货币情绪分析的MCP服务器。

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

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

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

  • 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.

  • Bora Yalcin
  • Evaluator for marketplace product descriptions, checks for relevancy and keyword stuffing.

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

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

  • 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.

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

  • Alexandru Strujac
  • Efficient thumbnail creator for YouTube videos

  • apappascs
  • 发现市场上最全面,最新的MCP服务器集合。该存储库充当集中式枢纽,提供了广泛的开源和专有MCP服务器目录,并提供功能,文档链接和贡献者。

  • Mintplex-Labs
  • 带有内置抹布,AI代理,无代理构建器,MCP兼容性等的多合一桌面和Docker AI应用程序。

  • modelcontextprotocol
  • 模型上下文协议服务器

  • n8n-io
  • 具有本机AI功能的公平代码工作流程自动化平台。将视觉构建与自定义代码,自宿主或云相结合,400+集成。

  • ShrimpingIt
  • MCP系列GPIO Expander的基于Micropython I2C的操作,源自ADAFRUIT_MCP230XX

  • WangRongsheng
  • 🧑‍🚀 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)|摘要世界上最好的LLM资源。

  • metorial
  • 数百个MCP服务器的容器化版本📡📡

  • open-webui
  • 用户友好的AI接口(支持Ollama,OpenAi API,...)

    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.