MCP server for analyzing OpenTelemetry traces
Project description
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
uv tool install otel-analyzer-mcp
Or for development:
uv sync
Usage
Run the server:
otel-analyzer-mcp
Or add to your MCP client config:
{
"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:
load_trace(path="/path/to/trace.json")
Search X-Ray:
search_xray(filter_expression='service("my-api") AND responseTime > 5', region="us-east-1")
Search GenAI traces:
search_genai_traces(filter_query='name like /bedrock/', region="us-east-1")
Load from CloudWatch:
load_trace(trace_id="abc123", source="cloudwatch", region="us-east-1")
Analyze performance:
analyze_perf(trace_id="abc123")
License
MIT
Project details
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