MCP server for Jaeger distributed tracing — search traces, inspect spans, compare traces, compute span statistics, map service dependencies.
Project description
jaeger-mcp
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 — 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 10 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
| Tool | Endpoint | Description |
|---|---|---|
jaeger_list_services |
GET /api/services |
List all instrumented services |
jaeger_list_operations |
GET /api/services/{service}/operations |
List operation names for a service |
jaeger_search_traces |
GET /api/traces |
Search traces with rich filters |
jaeger_get_trace |
GET /api/traces/{traceID} |
Full trace detail with span tree |
jaeger_get_dependencies |
GET /api/dependencies |
Service-to-service call graph |
jaeger_compare_traces |
GET /api/traces/{traceID} ×2 |
Structural diff between two traces |
jaeger_span_statistics |
GET /api/traces |
Per-operation latency and error stats |
jaeger_critical_path |
GET /api/traces/{traceID} |
Longest-duration span chain and bottleneck ranking |
jaeger_compare_windows |
GET /api/traces ×2 |
Aggregate trace behavior diff between two time periods |
jaeger_detect_anomalies |
GET /api/traces ×2 |
Statistical latency/error-rate spike detection per operation |
Installation
pip install jaeger-mcp
Or run directly without installing:
uvx jaeger-mcp
Configuration
All configuration is via environment variables:
| Variable | Required | Default | Description |
|---|---|---|---|
JAEGER_URL |
Yes | — | Jaeger query service URL, e.g. https://jaeger.example.com |
JAEGER_TOKEN |
No | — | Bearer token (takes precedence over Basic auth) |
JAEGER_USERNAME |
No | — | HTTP Basic auth username |
JAEGER_PASSWORD |
No | — | HTTP Basic auth password |
JAEGER_SSL_VERIFY |
No | true |
Set false for self-signed certificates |
JAEGER_TIMEOUT |
No | 30 |
HTTP request timeout in seconds |
JAEGER_RETRY_ATTEMPTS |
No | 3 |
Retry count for transient failures (0 to disable) |
JAEGER_CACHE_TTL |
No | 120 |
TTL 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-servicefrom 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
postgresmost frequently?" - "Compare trace
abc123against tracedef456— 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 fromjaeger_list_servicesoperation— narrow to a specific endpointtags— JSON string of tag filters, e.g.{"http.status_code":"500"}or{"error":"true"}start/end— time range in microseconds UTCmin_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 observedp50_duration_us,p95_duration_us,p99_duration_us— latency percentileserror_count,error_rate— errors (identified bytags["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:
- Jaeger Query Service API (
openapi.yaml) - Documents the actual Jaeger API endpoints - 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.Sessionwith connection pooling. - The session has
trust_env = Falseto 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_servicesandlist_operationsresponses are cached for 120 seconds (configurable viaJAEGER_CACHE_TTL).jaeger_search_tracespasseslimitdirectly to Jaeger — avoid requesting more traces than needed.jaeger_get_tracefetches the full trace in one call — large traces (thousands of spans) may be slow.jaeger_get_dependenciesaggregates 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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