OpenTelemetry MCP Server

Search for OpenTelemetry traces with filters. Supports both simple parameters and advanced generic filter system. Args: service_name: Filter by service name (use filters for advanced queries) operation_name: Filter by operation/span name start_time: Start time in ISO 8601 format (e.g., 2024-01-01T00:00:00Z) end_time: End time in ISO 8601 format min_duration_ms: Minimum trace duration in milliseconds max_duration_ms: Maximum trace duration in milliseconds gen_ai_system: Filter by LLM provider (e.g., openai, anthropic) gen_ai_request_model: Filter by requested model name (e.g., gpt-4) gen_ai_response_model: Filter by actual model used (e.g., gpt-4-0613) has_error: Filter traces with errors tags: Additional tag filters as key-value pairs filters: Generic filter conditions (advanced) - list of filter objects with: - field: Field name in dotted notation (e.g., "gen_ai.usage.prompt_tokens") - operator: Comparison operator (equals, not_equals, gt, lt, gte, lte, contains, not_contains, starts_with, ends_with, in, not_in, between, exists, not_exists) - value: Single value for most operators - values: List of values for "in", "not_in", "between" operators - value_type: Type of value(s) - "string", "number", or "boolean" limit: Maximum number of traces to return (1-1000, default: 100) Returns: JSON string with search results Filter Examples: Find expensive traces: {"field": "gen_ai.usage.total_tokens", "operator": "gt", "value": 5000, "value_type": "number"} Filter by multiple models: {"field": "gen_ai.request.model", "operator": "in", "values": ["gpt-4", "claude-3"], "value_type": "string"} Check if attribute exists: {"field": "gen_ai.request.temperature", "operator": "exists", "value_type": "number"} Find streaming requests: {"field": "gen_ai.request.is_streaming", "operator": "equals", "value": true, "value_type": "boolean"}

Get complete trace details by trace ID. Returns all spans with attributes, including parsed Opentelemetry data for LLM operations. Args: trace_id: Trace identifier Returns: JSON string with trace details

Get aggregated LLM usage metrics (token counts) for a time period. Provides breakdowns by model and service. Args: start_time: Start time in ISO 8601 format end_time: End time in ISO 8601 format service_name: Filter by service name gen_ai_system: Filter by LLM provider gen_ai_request_model: Filter by requested model name gen_ai_response_model: Filter by actual model used limit: Maximum traces to analyze (default: 1000) Returns: JSON string with usage metrics

List all available services in the OpenTelemetry backend. Returns: JSON string with list of services

Find traces with errors. Including detailed error messages, stack traces, and LLM-specific error information. Args: start_time: Start time in ISO 8601 format end_time: End time in ISO 8601 format service_name: Filter by service name limit: Maximum error traces to return (default: 100) Returns: JSON string with error traces