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Jaeger Mcp

mshegolev/jaeger-mcp
authSTDIOregistry active
Summary

Connects Claude to your Jaeger distributed tracing backend via the standard Query API. Exposes five read-only tools: list services and operations, search traces with filters (time range, tags, duration), fetch full trace details with span trees, and map service dependencies. Returns both JSON and Markdown for each query, so you can ask "show me 500 errors in order-service from the last hour" or "what called postgres most often this week" and get actionable answers. Supports Bearer tokens, HTTP Basic auth, or no auth for internal deployments. Useful when you're debugging production incidents in chat and need to pull trace data without context switching to the Jaeger UI.

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jaeger-mcp

PyPI version Python versions License: MIT Tests

MCP server for Jaeger distributed tracing. Give Claude (or any MCP-capable agent) read access to your trace data — search traces, inspect spans, compare traces, compute span statistics, map service dependencies, predict performance issues, and forecast capacity needs — without leaving the conversation.

Why another Jaeger MCP?

The existing Jaeger integrations require a running UI or custom scripts. This server:

  • Speaks the standard Model Context Protocol over stdio — works with Claude Desktop, Claude Code, Cursor, and any MCP client.
  • Is read-only: all 12 tools carry readOnlyHint: true — zero risk of modifying trace data.
  • Returns dual-channel output: structured JSON (structuredContent) for programmatic use + Markdown (content) for human-readable display.
  • Has actionable error messages that name the exact env var to fix and suggest a next step.
  • Supports Bearer token, HTTP Basic auth, or no auth (common for internal deployments).
  • Includes OpenAPI specification documenting the underlying Jaeger Query API (openapi.yaml).

Tools

ToolEndpointDescription
jaeger_list_servicesGET /api/servicesList all instrumented services
jaeger_list_operationsGET /api/services/{service}/operationsList operation names for a service
jaeger_search_tracesGET /api/tracesSearch traces with rich filters
jaeger_get_traceGET /api/traces/{traceID}Full trace detail with span tree
jaeger_get_dependenciesGET /api/dependenciesService-to-service call graph
jaeger_compare_tracesGET /api/traces/{traceID} ×2Structural diff between two traces
jaeger_span_statisticsGET /api/tracesPer-operation latency and error stats
jaeger_critical_pathGET /api/traces/{traceID}Longest-duration span chain and bottleneck ranking
jaeger_compare_windowsGET /api/traces ×2Aggregate trace behavior diff between two time periods
jaeger_detect_anomaliesGET /api/traces ×2Statistical latency/error-rate spike detection per operation
jaeger_predict_degradationGET /api/tracesPredict performance degradation 2-24 hours in advance
jaeger_forecast_capacityGET /api/tracesForecast throughput demands and resource requirements

Installation

pip install jaeger-mcp

Or run directly without installing:

uvx jaeger-mcp

Configuration

All configuration is via environment variables:

VariableRequiredDefaultDescription
JAEGER_URLYes—Jaeger query service URL, e.g. https://jaeger.example.com
JAEGER_TOKENNo—Bearer token (takes precedence over Basic auth)
JAEGER_USERNAMENo—HTTP Basic auth username
JAEGER_PASSWORDNo—HTTP Basic auth password
JAEGER_SSL_VERIFYNotrueSet false for self-signed certificates
JAEGER_TIMEOUTNo30HTTP request timeout in seconds
JAEGER_RETRY_ATTEMPTSNo3Retry count for transient failures (0 to disable)
JAEGER_CACHE_TTLNo120TTL in seconds for discovery endpoint cache (0 to disable)

Copy .env.example to .env and fill in your values.

Claude Desktop / Claude Code setup

Add to your MCP config (claude_desktop_config.json or .claude/mcp.json):

{
  "mcpServers": {
    "jaeger": {
      "command": "jaeger-mcp",
      "env": {
        "JAEGER_URL": "https://jaeger.example.com",
        "JAEGER_TOKEN": "your-token-here"
      }
    }
  }
}

Or with uvx (no install required):

{
  "mcpServers": {
    "jaeger": {
      "command": "uvx",
      "args": ["jaeger-mcp"],
      "env": {
        "JAEGER_URL": "https://jaeger.example.com"
      }
    }
  }
}

Docker

docker run --rm -e JAEGER_URL=https://jaeger.example.com jaeger-mcp

Example queries

Once configured, ask Claude:

  • "What services does Jaeger know about?"
  • "Find traces with HTTP 500 errors in order-service from the last hour"
  • "Show me the slowest traces (over 2 seconds) for GET /checkout"
  • "What caused the error in trace abcdef1234567890?"
  • "Map the service dependency graph for the last 7 days"
  • "Which services call postgres most frequently?"
  • "Compare trace abc123 against trace def456 — what spans changed?"
  • "What are the p95 latencies per operation in order-service?"

Tool usage guide

jaeger_list_services

Returns all service names Jaeger has seen. Start here when you don't know which services are instrumented. Output is capped at 500 services with a truncation hint.

jaeger_list_operations

Returns all operation names for a given service (e.g. HTTP route names, gRPC method names). Use to discover valid operation names before filtering jaeger_search_traces.

jaeger_search_traces

The main search tool. Filters:

  • service (required) — service name from jaeger_list_services
  • operation — narrow to a specific endpoint
  • tags — JSON string of tag filters, e.g. {"http.status_code":"500"} or {"error":"true"}
  • start / end — time range in microseconds UTC
  • min_duration / max_duration — duration strings like "100ms", "1.5s", "2m"
  • limit — default 20, max 1500

Returns trace summaries with trace_id, duration_us, span_count, service_count, root_operation, errors_count.

jaeger_get_trace

Full trace detail. Accepts a trace_id (hex string, 16-32 chars) and returns:

  • All spans with tags, service names, parent/child relationships
  • Per-service statistics (span count, total duration, error count)
  • Execution tree (each node lists its child span IDs)

Error spans are identified by tags["error"] = "true".

jaeger_get_dependencies

Service topology graph. Returns directed edges (parent → child) with call_count. Use lookback_hours (default 24, max 720) to control the window.

jaeger_compare_traces

Structural diff between two traces. Accepts two trace_id hex strings and matches spans by (operationName, serviceName, parentOperation) — not span ID. Reports:

  • Added spans — present in trace B but not trace A
  • Removed spans — present in trace A but not trace B
  • Changed spans — matched but differ in duration or tags (shows deltas)
  • Unchanged count — number of identical spans

Use to compare a slow trace against a fast one, or to see what changed between deployments.

jaeger_span_statistics

Per-operation latency percentiles and error rates. Fetches up to limit traces (default 20, max 100) for a service and aggregates all spans by operation name. Reports per operation:

  • count — total spans observed
  • p50_duration_us, p95_duration_us, p99_duration_us — latency percentiles
  • error_count, error_rate — errors (identified by tags["error"] = "true")

Use to find the slowest or most error-prone operations in a service.

jaeger_critical_path

Identifies the longest-duration span chain from root to leaf in a trace (the critical path) and ranks spans by self-time to find performance bottlenecks.

Reports:

  • Critical path spans with operation, service, duration, and percentage-of-total
  • Bottleneck spans ranked by exclusive duration (self-time)

Use to answer "Why is this trace so slow?" and "Which operations consume the most CPU/self-time?"

jaeger_compare_windows

Compares aggregate trace behavior between two time periods for a service to detect performance regressions or improvements across deployments.

Reports:

  • Per-operation diff summary showing added, removed, faster, slower operations
  • Deviation scoring with numeric scores per operation and overall
  • Latency percentile changes (p50, p95) and error rate deltas

Use to answer "Did our latest deployment affect performance?" and "Which operations got slower after the database upgrade?"

jaeger_detect_anomalies

Scans for statistically significant latency spikes or error-rate increases in a service's recent traces compared to historical baselines.

Reports:

  • Flagged operations with anomaly type (latency or error_rate)
  • Severity classification (low to critical) with z-scores
  • Current vs baseline values for affected metrics

Use to proactively identify performance degradations and reliability issues before they impact users.

Library facade (in-process use)

jaeger-mcp can also be used as a Python library without an MCP server:

from jaeger_mcp import JaegerClient

client = JaegerClient.from_env()  # reads JAEGER_URL from env
trace = client.get_trace("abcdef1234567890abcdef1234567890")

for span in trace.spans:
    if span.error:
        print(f"{span.service_name}: {span.operation} at {span.start_utc}")
        print(f"  tags: {span.tags}")

Available methods: get_trace(), search_traces(), list_services(), get_dependencies(), compare_traces(), span_statistics(), critical_path(), compare_windows(), detect_anomalies().

Domain objects: Span, Trace, TraceSummary, ServiceDep, TraceComparison, SpanIdentity, SpanChange, SpanStatisticsResult, OperationStatResult, CriticalPathOutput, CriticalPathSpan, BottleneckSpan, WindowComparisonOutput, OperationDiff, AnomalyDetectionOutput, OperationAnomaly — all with typed fields.

API Documentation

This project includes comprehensive OpenAPI specifications in the docs/ directory:

  1. Jaeger Query Service API (openapi.yaml) - Documents the actual Jaeger API endpoints
  2. MCP Tools API (docs/mcp-tools-openapi.yaml) - Documents the MCP tools as conceptual HTTP endpoints

These specifications are useful for:

  • Understanding the underlying API calls made by each tool
  • Developing alternative integrations
  • Debugging API interactions
  • Generating client libraries or documentation

See docs/README.md for more details on both specifications.

Performance characteristics

  • All tools use a single persistent requests.Session with connection pooling.
  • The session has trust_env = False to bypass environment proxies (Jaeger is typically an internal service).
  • Requests time out after 30 seconds (configurable via JAEGER_TIMEOUT).
  • Transient HTTP errors (429/5xx) are retried with exponential backoff (configurable via JAEGER_RETRY_ATTEMPTS).
  • list_services and list_operations responses are cached for 120 seconds (configurable via JAEGER_CACHE_TTL).
  • jaeger_search_traces passes limit directly to Jaeger — avoid requesting more traces than needed.
  • jaeger_get_trace fetches the full trace in one call — large traces (thousands of spans) may be slow.
  • jaeger_get_dependencies aggregates over the full lookback window; large windows may be slow on busy clusters.

Development

git clone https://github.com/mshegolev/jaeger-mcp
cd jaeger-mcp
pip install -e '.[dev]'
pytest tests/ -v
ruff check src tests
ruff format src tests

License

MIT — see LICENSE.

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Configuration

JAEGER_URL*

Jaeger query service URL, e.g. https://jaeger.example.com

JAEGER_TOKENsecret

Bearer token for authentication. Takes priority over Basic auth.

JAEGER_USERNAME

HTTP Basic auth username. Used only when JAEGER_TOKEN is not set.

JAEGER_PASSWORDsecret

HTTP Basic auth password.

JAEGER_SSL_VERIFYdefault: true

Verify SSL certificates (true/false). Set to 'false' for self-signed certs.

Categories
Search & Web Crawling
Registryactive
Packagejaeger-mcp
TransportSTDIO
AuthRequired
UpdatedApr 18, 2026
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