Crypto Sentiment MCP Server

What does “Crypto Sentiment” MCP Server do?

The Crypto Sentiment MCP Server is a specialized tool designed to provide AI agents with real-time and historical sentiment analysis for cryptocurrencies. By leveraging Santiment’s aggregated social media and news data, the server enables AI-driven workflows to track market mood, detect emerging trends, and analyze the discourse around various crypto assets. This MCP server acts as a bridge between AI assistants and external sentiment data sources, facilitating enhanced decision-making and automation for developers and traders. With features such as sentiment balance, social volume tracking, trending word identification, and dominance measurement, Crypto Sentiment MCP Server empowers users to perform data-driven cryptocurrency analysis within their AI development environments.

List of Prompts

No prompt templates were listed in the repository or documentation.

List of Resources

No explicit resources were detailed in the repository or documentation.

List of Tools

• get_sentiment_balance: Retrieves the average sentiment balance (positive vs. negative) for a specific cryptocurrency asset over a defined period.
• get_social_volume: Fetches the total number of social media mentions for a given crypto asset over a set number of days.
• alert_social_shift: Detects significant spikes or drops in social volume for an asset compared to its previous average, based on a specified threshold.
• get_trending_words: Returns the top trending words or terms in cryptocurrency discussions, ranked by score over a specified period.
• get_social_dominance: Measures the percentage of crypto media discussions dominated by a particular asset over a given timeframe.

Use Cases of this MCP Server

• Market Sentiment Analysis: Enables developers and traders to gauge the prevailing mood in the crypto market for specific assets, supporting informed trading strategies.
• Trend Detection: Identifies emerging topics and trending assets by analyzing trending words and social volume, aiding in the early detection of market-moving events.
• Volatility Alerts: Automatically detects and alerts users to sudden changes in social media activity, which often precede significant price movements.
• Portfolio Monitoring: Allows AI agents to monitor sentiment and dominance for assets in a user’s portfolio, supporting proactive portfolio management.
• Community Engagement Analysis: Helps community managers and marketers understand which projects and terms are gaining traction or losing relevance in the crypto space.

How to set it up

Windsurf

1. Ensure prerequisites: Install Python 3.10+ and obtain a Santiment API Key.
2. Clone the repository:

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

3. Locate configuration: Open your Windsurf configuration file.
4. Add the MCP server:

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

5. Save and restart Windsurf to load the server.

Claude

1. Install Python 3.10+ and obtain Santiment API key.
2. Clone the repository and navigate to its directory.
3. Edit configuration file for Claude.
4. Add server entry:

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

5. Restart Claude and verify server connection.

Cursor

1. Install Python 3.10+ if needed and obtain API key.
2. Clone the repo and navigate to its folder.
3. Open Cursor’s config file.
4. Insert the MCP config:

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

5. Restart Cursor to enable the MCP server.

Cline

1. Ensure Python 3.10+ is installed and get your Santiment API key.
2. Clone the repo to your chosen directory.
3. Edit Cline’s configuration.
4. Add this snippet:

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

5. Save and restart to verify server is running.

Securing API Keys

Store sensitive keys using environment variables in the env field of your MCP server config:

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

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "crypto-sentiment-mcp": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “crypto-sentiment-mcp” to whatever the actual name of your MCP server is, and replace the URL with your own MCP server URL.

Overview

| Roots Support | ⛔ | Not mentioned |

Based on the tables above, Crypto Sentiment MCP Server has strong documentation on its core functionality and setup, but lacks prompt templates, resource definitions, and explicit mention of MCP advanced features like roots and sampling. For crypto sentiment workflows it is highly usable, though it could benefit from additional resources and prompt workflow support.

MCP Score