MCP server for analyzing OpenTelemetry traces
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# OTEL Analyzer MCP Server MCP server for analyzing OpenTelemetry traces with performance and error diagnosis. ## Features - Load traces from files, strings, AWS X-Ray, or CloudWatch GenAI observability - Auto-detect format (OTLP JSON, Jaeger, Protobuf, X-Ray) - Performance analysis: latency breakdown, slow spans, critical path - Error analysis: error detection, exception extraction, context - GenAI trace analysis: Bedrock AgentCore, token usage, model latency - MCP sampling for LLM-assisted deep analysis ## Installation ```bash uv tool install otel-analyzer-mcp ``` Or for development: ```bash uv sync ``` ## Usage Run the server: ```bash otel-analyzer-mcp ``` Or add to your MCP client config: ```json { "mcpServers": { "otel-analyzer-mcp": { "command": "otel-analyzer-mcp" } } } ``` ## Tools | Tool | Description | |------|-------------| | `load_trace` | Load from file, JSON, X-Ray trace ID, or CloudWatch | | `search_xray` | Search X-Ray with filter expressions | | `search_genai_traces` | Search CloudWatch aws/spans for GenAI traces | | `list_traces` | List all loaded traces | | `analyze_perf` | Performance analysis (latency, slow spans, critical path) | | `analyze_errs` | Error analysis (errors, exceptions, context) | | `summarize_trace` | High-level trace overview | | `deep_analyze` | LLM-assisted analysis via MCP sampling | ## Examples Load a trace file: ```text load_trace(path="/path/to/trace.json") ``` Search X-Ray: ```text search_xray(filter_expression='service("my-api") AND responseTime > 5', region="us-east-1") ``` Search GenAI traces: ```text search_genai_traces(filter_query='name like /bedrock/', region="us-east-1") ``` Load from CloudWatch: ```text load_trace(trace_id="abc123", source="cloudwatch", region="us-east-1") ``` Analyze performance: ```text analyze_perf(trace_id="abc123") ``` ## License MIT
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