Observability AIops
FreeNot checkedGoverned Prometheus + Grafana ops: PromQL, alerts, dashboards, RCA; 39 tools.
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Governed Prometheus + Grafana ops: PromQL, alerts, dashboards, RCA; 39 tools.
README
Observability AIops
Disclaimer: Community-maintained open-source project. Not affiliated with, endorsed by, or sponsored by the Prometheus or Grafana projects, Grafana Labs, or the Cloud Native Computing Foundation. Prometheus, Alertmanager and Grafana are trademarks of their respective owners. MIT licensed.
Governed AI-ops for a self-hosted observability stack in one server —
Prometheus (HTTP API, PromQL, targets, rules, alerts), Alertmanager
(alerts + silences), Grafana (dashboards, datasources, folders), and
Grafana Loki (bounded LogQL log reads + log RCA) — with a built-in
governance harness: unified audit log, token/runaway budget
guard, undo-token recording, and descriptive risk-tier labels. One config can
span your whole stack; each target names its own platform.
Beyond the mock test suite, the Prometheus/Alertmanager/Grafana reads, the RCAs,
and the governed silence + dashboard write paths (with undo) have been exercised against a live Prometheus 3.x + Alertmanager + Grafana 13 stack — see
docs/VERIFICATION.md.
This is the self-hosted-observability complement to enterprise monitoring suites: it speaks the open Prometheus/Grafana APIs an SRE actually runs, not a vendor NMS.
What it does
Answers the questions an SRE actually repeats over a Prometheus/Grafana stack, and guards the writes that follow:
- PromQL + metadata — instant and range queries, label-value enumeration, and series metadata, all read-only and result-capped.
- Scrape-target & rule health — which targets are up/down (and why, from
lastError), which were dropped by relabeling, and which recording/alerting rules are erroring. - Alerts & silences — firing/pending Prometheus rule alerts, Alertmanager's post-routing view, and its silences.
- Grafana — dashboards, datasources (+ health), and folders.
- Loki logs — bounded LogQL reads (label + label-value enumeration, a
validation-gated
query_range, and a canned error-tail), all read-only with a hard lookback + line cap, optional multi-tenantX-Scope-OrgID, and basic/bearer auth per target. - Flagship analyses — transparent heuristics that show their numbers:
firing_alert_rca(join each firing alert to its rule expr → cause + action),target_scrape_health_analysis(rank down/erroring scrapes → likely cause),alert_noise_and_flap_analysis(frequently-repeated / duplicate alerts → dedup/rollup recommendation), plus two log analyses —log_error_burst_rca(per-stream error burst vs baseline → new-signature / volume-spike / single-instance) andlog_volume_analysis(top streams + high-cardinality label warnings + retention hint) — andalert_log_context, which correlates a firing Prometheus alert to its Loki streams. - Governed writes — create/expire Alertmanager silences (time-boxed), create
Grafana annotations, update/delete dashboards, and hot-reload the Prometheus
config — each audited, risk-tiered,
dry_run-able, and the reversible ones capture the real fetched before-state for undo.
What this tool does, and does not, decide
It delivers Prometheus + Grafana operations — reads and writes — accurately and efficiently, and records every one of them. It does not decide whether a write is allowed to happen. That is the agent's judgement, or the permission of the account you connect it with: give it a Grafana token with only Viewer scope, and a Prometheus/Alertmanager reached without the admin/write API, and the writes fail at the server — the place that actually owns the permission.
So there is no read-only switch, no policy file, no approval gate to configure. The one thing the
tool guarantees is that nothing is silent: every call, over MCP and over the CLI alike, lands
an audit row in ~/.observability-aiops/audit.db, and destructive writes still capture their
before-state and record an inverse where one exists.
Each tool declares a
risk_level, carried into the audit row as a descriptive tier (none/confirm/review) — so a reviewer can see at a glance that a row was a high-risk delete. It is a label, not a gate.
Capability matrix (39 MCP tools)
| Group | Platform | Tools | Count | R/W |
|---|---|---|---|---|
| Metrics | Prometheus | instant_query, range_query, label_values, series_metadata |
4 | read |
| Targets | Prometheus | list_targets, target_scrape_health, dropped_targets |
3 | read |
| Status | Prometheus | prometheus_config_status, prometheus_tsdb_status |
2 | read |
| Rules | Prometheus | list_rules, rule_health |
2 | read |
| Alerts | Prometheus/Alertmanager | firing_alerts, pending_alerts, alertmanager_alerts, list_silences |
4 | read |
| Grafana | Grafana | list_dashboards, get_dashboard, list_datasources, datasource_health, list_folders |
5 | read |
| Loki | Loki | loki_labels, loki_label_values, loki_query, loki_tail_errors |
4 | read |
| Overview | all | observability_overview |
1 | read |
| Analyses | Prometheus | firing_alert_rca, target_scrape_health_analysis, alert_noise_and_flap_analysis |
3 | read |
| Log analyses | Loki | log_error_burst_rca, log_volume_analysis |
2 | read |
| Cross-signal | Prometheus + Loki | alert_log_context |
1 | read |
| Writes | Alertmanager | create_silence, expire_silence |
2 | write (med) |
| Grafana | create_annotation |
1 | write (medium) | |
| Grafana | update_dashboard |
1 | write (med) | |
| Grafana | delete_dashboard |
1 | write (high) | |
| Prometheus | reload_prometheus_config |
1 | write (med) | |
| Undo | all | undo_list |
1 | read |
| all | undo_apply |
1 | write (med) |
Loki is read-only — Loki exposes no safe operational write surface (no silence/annotation analogue), so this tool deliberately ships no Loki writes.
The CLI exposes a convenience subset (query, logs, alert, overview, …);
the full 39-tool surface is via the MCP server.
Quick start
uv tool install observability-aiops # or: pipx install observability-aiops
observability-aiops init # wizard: pick platform (prometheus/grafana) + store the token (encrypted)
observability-aiops doctor # verify config, secrets, connectivity
observability-aiops overview # snapshot: firing alerts + targets up/down + rules erroring
observability-aiops query instant 'up' # run a PromQL instant query
observability-aiops logs errors '{app="api"}' # tail error-level Loki logs (bounded)
observability-aiops alert rca # root-cause the firing alerts
Run as an MCP server (stdio):
export OBSERVABILITY_AIOPS_MASTER_PASSWORD=... # unlock secrets non-interactively
observability-aiops mcp
Governance
Every MCP tool passes through the bundled @governed_tool harness:
- Audit — every call (params, result, status, duration, risk tier, and any operator-supplied
approver/rationale) is logged to
~/.observability-aiops/audit.db(relocatable viaOBSERVABILITY_AIOPS_HOME). The CLI writes the same row the MCP path does — there is no unaudited entry point. - Runaway guard — a safety backstop, not an authorization gate: the same call hammered in a
tight loop trips a circuit breaker. Disable with
OBSERVABILITY_RUNAWAY_MAX=0; optional hard ceilings viaOBSERVABILITY_MAX_TOOL_CALLS/OBSERVABILITY_MAX_TOOL_SECONDS. - Undo recording — reversible writes record an inverse descriptor built from the fetched
before-state (
create_silence→expire,update_dashboard/delete_dashboard→restore the captured prior model). - Risk tier — a descriptive label on the audit row derived from
risk_level; it gates nothing.
Supported scope & limitations
- Platforms: Prometheus HTTP API (+ a companion Alertmanager), Grafana HTTP API, and Grafana Loki HTTP API (read-only). Hosted/SaaS monitoring suites (Datadog, New Relic, enterprise NMS) are deliberately out of scope for this tool.
- Verification. The mock suite covers all four platforms; in addition the
Prometheus, Alertmanager and Grafana surfaces have been exercised against a live Prometheus 3.x + Alertmanager + Grafana 13 stack (RCAs, the
silence and dashboard governed writes, and undo replay). The Loki surface
has not yet been exercised live. All four are free and open-source and trivial
to stand up in a lab (
docker run prom/prometheus,grafana/grafana,grafana/loki), soobservability-aiops doctoris the fastest live check (Prometheus/api/v1/status/buildinfo, Grafana/api/health, Loki/ready+/loki/api/v1/status/buildinfo). See docs/VERIFICATION.md.
Missing a capability?
Want another read, an analysis tuned, or a platform capability that isn't here? Open an issue or a PR — feedback and contributions are welcome.
Install Observability AIops in Claude Desktop, Claude Code & Cursor
unyly install observability-aiopsInstalls into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.
First time? Get the CLI: curl -fsSL https://unyly.org/install | sh
Or configure manually
Run in your terminal:
claude mcp add observability-aiops -- uvx observability-aiopsStep-by-step: how to install Observability AIops
FAQ
Is Observability AIops MCP free?
Yes, Observability AIops MCP is free — one-click install via Unyly at no cost.
Does Observability AIops need an API key?
No, Observability AIops runs without API keys or environment variables.
Is Observability AIops hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install Observability AIops in Claude Desktop, Claude Code or Cursor?
Open Observability AIops on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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