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Crypto Sentiment MCP Server: Real-Time Sentiment, Actionable Edge - MCP Implementation

Crypto Sentiment MCP Server: Real-Time Sentiment, Actionable Edge

Empower AI agents with real-time crypto sentiment analysis. Boost decisions with MCP Server’s accurate, actionable insights—your edge in volatile markets.

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This tool saved users approximately 12425 hours last month!

About Crypto Sentiment MCP Server

What is Crypto Sentiment MCP Server: Real-Time Sentiment, Actionable Edge?

Crypto Sentiment MCP Server is an advanced analytical tool designed to empower AI-driven decision-making in cryptocurrency markets. By aggregating real-time data from social media, news platforms, and trading activity via Santiment’s robust infrastructure, it delivers granular insights into market sentiment and behavioral patterns. This server acts as a bridge between raw data and actionable intelligence, enabling users to preempt market movements and optimize trading strategies with precision.

How to Use Crypto Sentiment MCP Server: Real-Time Sentiment, Actionable Edge?

To leverage this tool, users must first install the server environment and configure access to Santiment’s API. After setting up the required Python dependencies, the server can be deployed to process incoming data streams. Interaction occurs via standardized API endpoints or direct integration with existing AI platforms. For example, querying the server for “BTC sentiment balance” instantly returns a sentiment score derived from thousands of data points, enabling proactive adjustments to trading algorithms.

Crypto Sentiment MCP Server Features

Key Features of Crypto Sentiment MCP Server: Real-Time Sentiment, Actionable Edge?

  • Sentiment Balance Analysis: Quantifies bullish/bearish sentiment through NLP-driven evaluation of social media and news content.
  • Granular Social Volume Tracking: Monitors transactional and discourse activity across exchanges and forums in near real-time.
  • Market Dominance Metrics: Calculates relative influence of specific cryptocurrencies using network and sentiment data.
  • Trendword Profiling: Identifies emerging keywords and their correlation with price movements, offering early indicators of market shifts.

Use Cases of Crypto Sentiment MCP Server: Real-Time Sentiment, Actionable Edge?

Traders utilize sentiment scores to time entries/exit points during volatile periods. Portfolio managers employ dominance metrics to rebalance allocations, while analysts track trendwords to uncover undervalued projects. For instance, detecting sudden spikes in “DeFi” mentions paired with rising whale activity might signal an altcoin pump. Institutions use this data to validate macroeconomic hypotheses or stress-test risk models against behavioral anomalies.

Crypto Sentiment MCP Server FAQ

FAQ from Crypto Sentiment MCP Server: Real-Time Sentiment, Actionable Edge?

  • Q: Does the server require manual data preprocessing?
    A: No. The system automatically cleanses and normalizes data streams from Santiment’s sources, ensuring AI compatibility.
  • Q: Can it integrate with existing trading bots?
    A: Yes. RESTful API endpoints allow plug-and-play integration with platforms like TradingView, QuantConnect, or custom solutions.
  • Q: What’s the latency between data capture and analysis?
    A: Sub-5-second processing for most metrics, ensuring real-time relevance for high-frequency strategies.
  • Q: How is API access priced?
    A: Tiered pricing based on query volume; enterprise plans include dedicated support and SLAs. Visit Santiment’s website for details.

Content

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

  1. 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.

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