get_correlation_matrix
Analyze correlation coefficients between multiple cryptocurrency tokens over specified timeframes to identify price movement relationships.
Instructions
Get correlation matrix between multiple tokens.
Args: tokens: List of token addresses or symbols to analyze timeframe: Analysis period. Options: 1d, 7d, 30d, 90d
Returns: Correlation coefficients between all token pairs.
Price: $0.50
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| tokens | Yes | ||
| timeframe | No | 7d |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Implementation Reference
- coinrailz_mcp/__init__.py:427-443 (handler)The MCP tool handler for "get_correlation_matrix", which accepts a list of tokens and a timeframe, calls the internal `call_coinrailz_service` helper, and returns the correlation data as a JSON string.
@mcp.tool() async def get_correlation_matrix(tokens: List[str], timeframe: str = "7d") -> str: """ Get correlation matrix between multiple tokens. Args: tokens: List of token addresses or symbols to analyze timeframe: Analysis period. Options: 1d, 7d, 30d, 90d Returns: Correlation coefficients between all token pairs. Price: $0.50 """ payload = {"tokens": tokens, "timeframe": timeframe} result = await call_coinrailz_service("correlation-matrix", payload) return json.dumps(result, indent=2)