TraceDelta
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@TraceDeltainvestigate high error rate in checkout-service"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
TraceDelta
A shared, source-verifiable evidence-memory layer for AI operations — over SigNoz.
Built for the WeMakeDevs "Agents of SigNoz" hackathon.
Today, multiple AI agents and engineers investigating the same production incident each re-query the same logs, traces, and metrics — wasting LLM context, telemetry work, and reaching inconsistent conclusions. TraceDelta sits between AI agents and SigNoz and turns a bounded investigation into a versioned, source-linked evidence capsule:
incident scope (env, services, time range, symptom) as a canonical identity;
typed claims — observed facts, comparisons, correlations, hypotheses, action-candidates, and explicit known-unknowns (never one confident blob);
evidence references (trace ids, span ids, log clusters, metric queries, alerts);
freshness timestamps and a delta showing what changed since the last version;
a savings ledger: reused evidence, duplicate queries avoided, context reduction.
It is not a generic "AI summary of logs" and not another dashboard. It is a reusable, evidence-linked, freshness-aware investigation artifact that routes back to the exact telemetry.
Validation status (honest)
Validated against live, self-hosted SigNoz v0.134.0 (not SigNoz Cloud), deployed
by Foundry — full detail and evidence in docs/validation.md
and docs/live-evidence/.
✅ Foundry installs SigNoz + its MCP server (
spec.mcp.spec.enabled: true→ forgedsignoz-mcp); stack healthy, ran 11h+.✅ Real ingestion from the demo —
checkout-service/payment-servicewith 100% error rate, real 502 error logs and traces (root spansPOST /checkout~1.25s).✅ TraceDelta ↔ live SigNoz (REST adapter, v0.134) — full flow on real data:
start_investigation(100% error rate, p95 5.9× baseline) → reuse → delta →verify_claim(supported) →drill_down(live trace + deep link) → savings (30.6× context compression, 6 duplicate queries avoided).✅ TraceDelta's own OTel in SigNoz —
tracedelta-mcpappears as a service withstart_investigation/refresh_capsulespans (the closed loop).✅ Official SigNoz MCP server completes an
initializehandshake at:8000/mcp.✅ Fixture tier — 24 unit tests;
make demo(25.5× compression); image builds.✅ Screenshots (headless Chromium, real) — SigNoz Services + Traces of the live incident, and the TraceDelta capsule / delta / evidence-drawer / savings surfaces. See
docs/live-evidence/screenshots/.
The default FixtureSigNoz backend reproduces the incident shape so the demo/tests
run with no backend — the blueprint-sanctioned adapter fallback (§15).
Related MCP server: agent-debugger
The 30-second proof
make install # uv venv + deps (Python 3.12)
make test # 24 tests: matching, versioning, delta, redaction, evidence links
make demo # two agents investigate one incident, end-to-end
make web # http://127.0.0.1:8700 — inspect the capsule visuallymake demo shows: Agent A opens a capsule → Agent B reuses it (no re-query) →
refresh returns a delta (retries increased, no new signature) → verify_claim
routes to source evidence → drill_down returns a redacted raw trace →
report_savings reports duplicate queries avoided and ~20×+ context compression.
MCP tools
Tool | What it does | Safety |
| Begin or reuse a bounded investigation → capsule | read-only |
| Candidates for a scope | never auto-merges |
| Situation, typed claims, evidence, freshness, consumers | respects policy |
| Change-only delta + new version | read-only |
| Supporting + contradicting source evidence | shows query context |
| Bounded raw evidence | redaction + field allow-list |
| Structured version diff | no causal inference |
| Reuse / avoided queries / compression | estimates labelled |
Connect Claude Code with the shipped .mcp.json (/mcp → tracedelta), or over
HTTP with make mcp-http. See docs/mcp-config.md.
Architecture
Full diagram and request flow in docs/architecture.md.
AI clients / humans ─► TraceDelta MCP server ─► SigNoz (OTel: traces·logs·metrics·alerts)
│ resolver (deterministic canonical key)
│ evidence compiler (refs → typed claims)
│ delta engine · policy+redaction · savings ledger
└ SQLite (capsules · claims · evidence · deltas)
TraceDelta also emits its OWN OpenTelemetry back into SigNoz (the closed loop)Deterministic matching — a human-inspectable canonical key (
backend | org | env | service-set | time-window | symptom-kind | signature | intent), not an LLM guess. Related-but-not-identical investigations are surfaced, never merged.Object model — Investigation 1─N Capsule versions, Capsule 1─N Claims, Claim N─N Evidence, Capsule 1─N Deltas, Capsule 1─1 Policy.
Persistence — SQLite (local-first, inspectable), full version history.
SigNoz integration (and the Foundry deployment)
The final deployment target is self-hosted SigNoz (not SigNoz Cloud), installed
by Foundry. casting.yaml enables the MCP component, so foundryctl installs
and runs both SigNoz and the official SigNoz MCP server (signoz-mcp on
signoz-network:8000):
spec:
deployment: { flavor: compose, mode: docker }
mcp:
spec:
enabled: true # Foundry installs signoz/signoz-mcp-server alongside SigNozTraceDelta consumes SigNoz through documented SigNoz REST APIs behind a clean
adapter (blueprint §15); the Foundry-managed signoz-mcp is available for agents
to call directly at http://localhost:8000/mcp. Both live behind one
SigNozClient interface, and a deterministic FixtureSigNoz implements the same
interface so the demo/tests need no running backend.
make gauge # foundryctl gauge — validate tools
make signoz-up # foundryctl forge (→ casting.yaml.lock + pours/) + docker compose up (SigNoz + MCP)
make stack-up # overlay: demo app + TraceDelta MCP + web (wired to self-hosted SigNoz)casting.yaml and casting.yaml.lock are committed; pours/ (the generated
compose stack + configs) is regenerable with make forge. Full-stack endpoints and
the incident load generator are documented in DEMO.md.
Demo incident
checkout-service → payment-service → simulated external stripe provider
(demo/). The load generator runs baseline traffic, emits a deploy marker
(checkout-service@v2.4.1), then flips the provider into timeout mode: checkout
502s rise, retries climb, timeout spans dominate. TraceDelta correctly reports the
deploy as correlation, not causation, and names the safe next verification step.
Security & trust
Read-only MVP — no writes to production systems.
Redaction before storage/display — emails, bearer tokens, API keys, JWTs, card- and secret-like values are stripped before they reach SQLite; trace/span ids are preserved as references.
Evidence-backed — every material claim carries ≥1 source reference.
Honest gaps — missing evidence or an unreachable backend is stated plainly; TraceDelta never invents a root cause.
Typed uncertainty — facts, correlations, hypotheses, and unknowns stay distinct.
Tests
make testCovers deterministic matching, capsule versioning, delta generation, redaction
(incl. that raw secrets never reach the store), and claim↔evidence links. A sample
capsule is in docs/sample_capsule.json.
Project layout
tracedelta/ core: identity · redaction · models · db · resolver · compiler
· delta · savings · service · mcp_server · web · otel
signoz/ SigNozClient: base · fixture (deterministic) · api (real REST)
demo/ checkout-service · payment-service · loadgen (OTel-instrumented)
scripts/ demo.py (end-to-end) · gen_sample.py
tests/ matching · versioning · delta · redaction · evidence links
deploy/ tracedelta.compose.yaml (overlay onto Foundry's signoz-network)
casting.yaml(.lock) SigNoz deployment via Foundry
docs/ architecture.md · mcp-config.md · validation.md · live-evidence/The product blueprint that guided this build (vision, security model, spec) is kept private and is not part of this repository.
Limitations (MVP, by design)
Deferred per blueprint §11: universal semantic matching of arbitrary questions, autonomous remediation/writes, multi-tenant sharing, exact provider-billing reconciliation, and automatic root-cause claims. The real SigNoz REST adapter is best-effort and version-sensitive; the fixture backend is the guaranteed demo path.
AI-assistance disclosure
See DISCLOSURE.md.
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