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An MCP server that delivers cryptocurrency sentiment analysis to AI agents.
Configuration
View docs{
"mcpServers": {
"kukapay-crypto-sentiment-mcp": {
"command": "uv",
"args": [
"--directory",
"path/to/crypto-sentiment-mcp",
"run",
"main.py"
],
"env": {
"SANTIMENT_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}This MCP server delivers cryptocurrency sentiment analysis and social metrics to AI agents by integrating Santiment’s data, enabling you to track market mood, monitor social volume, and surface trending terms for selected assets.
You interact with this server through an MCP client. Ask for sentiment, social volume, dominance, or trending words for a specific cryptocurrency, and you receive concise, actionable results. Use plain language queries like: “What is Bitcoin’s sentiment balance over the last 7 days?” or “Show Ethereum’s social volume for the past 5 days.” The server computes the asked metric by calling the available tools and returns a straightforward result.
Prerequisites include Python 3.10 or higher and a Santiment API key.
Clone the MCP server repository and prepare your environment.
git clone https://github.com/kukapay/crypto-sentiment-mcp.git
cd crypto-sentiment-mcpConfigure the MCP client to run the server locally by providing the runtime command, the directory path to the server, and your Santiment API key.
{
"mcpServers": {
"crypto-sentiment-mcp": {
"command": "uv",
"args": ["--directory", "path/to/crypto-sentiment-mcp", "run", "main.py"],
"env": {
"SANTIMENT_API_KEY": "your_api_key_here"
}
}
}
}The above configuration shows how to start the server locally using the MCP runner. The environment variable SANTIMENT_API_KEY must be provided with your Santiment key. The command uses uv to execute the server located in the specified directory.
This MCP server exposes a set of endpoints (tools) to fetch analytics for assets. The available tools are:
Get the average sentiment balance for an asset over a specified period.
Fetch the total number of social media mentions for an asset.
Detect significant spikes or drops in social volume compared to the previous average.
Retrieve the top trending words in crypto discussions, ranked by score over a period.
Measure the percentage of crypto media discussions dominated by an asset over a period.