List all metric names known to Prometheus, with optional substring filter.

Wraps GET /api/v1/label/__name__/values. Prometheus returns all metric names at once — no pagination. Output is capped at 500 metrics after filtering, with a truncation hint when more exist.

Use this first to discover valid metric names before writing PromQL expressions for prometheus_query or prometheus_query_range.

Examples: - Use when: "What metrics does Prometheus have about HTTP requests?" → pattern='http'; read the metrics list. - Use when: "List all node_exporter metrics" → pattern='node_'. - Use when: Starting a monitoring investigation — list metrics first to discover what's instrumented, then query specific ones. - Don't use when: You already know the exact metric name and want to query its value (call prometheus_query directly — one fewer round trip). - Don't use when: You want to see current alert state (call prometheus_list_alerts).

Returns: dict with total_count / returned_count / truncated / pattern / metrics (sorted list).

Execute an instant PromQL query against Prometheus.

Wraps GET /api/v1/query. Returns the result type (vector, scalar, matrix, string) and a list of samples each carrying labels, timestamp, and value. For vector results each element is one time series at the evaluation instant.

Examples: - Use when: "Is the payment service up right now?" → query='up{job="payment-service"}'. - Use when: "What is the current HTTP request rate?" → query='sum(rate(http_requests_total[5m])) by (job)'. - Use when: "Show me all metrics for a specific instance" → query='{instance="localhost:9090"}'. - Don't use when: You want to see how a metric changed over time (call prometheus_query_range with start/end/step). - Don't use when: You don't know the metric name yet (call prometheus_list_metrics first to discover names).

Returns: dict with query / time / result_type / result_count / data (list of samples with labels, timestamp, value).

Execute a PromQL range query returning time-series data points.

Wraps GET /api/v1/query_range. Returns one series per matching time series, each with labels and a list of [timestamp, value] pairs. Total points across all series are capped at 5000 with a truncation hint.

Prometheus may reject the query with HTTP 422 (bad_data) if the step produces too many data points (> 11,000 per series). Increase the step or narrow the time range if this happens.

Note: The Prometheus API does not support filtering by branch or commit in this endpoint — filters are expressed purely in PromQL label matchers.

Examples: - Use when: "Show me CPU usage over the last hour with 1-minute resolution" → query='rate(node_cpu_seconds_total[5m])', step='1m'. - Use when: "Graph HTTP error rate for the last 24 hours" → query='rate(http_requests_total{status=~"5.."}[5m])', start='2024-01-15T00:00:00Z', end='2024-01-16T00:00:00Z', step='5m'. - Use when: Investigating a past incident — pick the time window of the incident and use a fine step. - Don't use when: You only want the current value (call prometheus_query — faster and simpler). - Don't use when: You want alert history (call prometheus_list_alerts).

Returns: dict with query / start / end / step / result_type / series_count / total_points / truncated / data (list of series with labels, point_count, values).

List all active and pending alerts from Prometheus.

Wraps GET /api/v1/alerts. Returns every alert that Prometheus currently tracks, with labels (including alertname, severity), state (firing / pending), the time it became active, and its current value. Also returns a summary grouped by state and a count by severity label.

Examples: - Use when: "Are there any firing alerts right now?" → check firing_count and alerts where state='firing'. - Use when: "Show me all critical alerts" → filter alerts by labels.severity == 'critical'. - Use when: Checking system health during an incident — list alerts first to understand what's firing before querying metrics. - Don't use when: You want historical alert data (Prometheus stores only current state; use Alertmanager or a recording rule for history). - Don't use when: You want raw metric values (call prometheus_query or prometheus_query_range).

Returns: dict with total_count / firing_count / pending_count / state_summary / alerts (list with labels, annotations, state, active_at, value). Enhanced with correlation information when requested.

List Prometheus scrape targets, summarised by job and health.

Wraps GET /api/v1/targets. Returns scrape targets with job name, instance address, health status (up / down / unknown), last scrape duration in milliseconds, and any last error. Also returns a summary grouped by job and health state.

Examples: - Use when: "Which targets are currently down?" → filter targets where health='down' and check last_error. - Use when: "How many instances of the 'node-exporter' job are up?" → check job_summary for the 'node-exporter' entry. - Use when: Investigating a scrape failure — list targets for the affected job to see which instances have errors. - Don't use when: You want metric values from a target (call prometheus_query with label matchers instead). - Don't use when: You want alert status (call prometheus_list_alerts instead).

Returns: dict with state_filter / total_count / up_count / down_count / unknown_count / job_summary (per-job health counts) / targets (list with job, instance, health, last_scrape_duration_ms, last_error, labels).

Get metric metadata (HELP text, TYPE, UNIT) from Prometheus.

Wraps GET /api/v1/metadata. Returns the metadata that Prometheus scraped from HELP, TYPE, and UNIT lines in the exposition format. Each metric may have multiple metadata entries if different scrape targets expose different help strings.

Use this to understand what a metric measures, its type (counter, gauge, histogram, summary), and unit — essential for writing correct PromQL. For example, knowing a metric is a counter means you should use rate() or increase(); a gauge can be used directly.

Examples: - Use when: "What does http_requests_total measure?" → metric='http_requests_total'; read help and type. - Use when: "Show me all histogram metrics" → call with no filter; filter results where type='histogram'. - Use when: Starting an investigation — check metric types before writing PromQL to avoid using rate() on a gauge. - Don't use when: You already know the metric type and want to query values (call prometheus_query directly).

Returns: dict with metric / total_count / returned_count / truncated / metadata (dict of metric name → list of {type, help, unit}).

List all values for a specific label from Prometheus.

Wraps GET /api/v1/label/{label_name}/values. Returns all distinct values for the named label across all time series, optionally filtered by a series selector.

Use this to discover what entities exist for a given label dimension — for example, which jobs are running, which instances are scraped, or which namespaces have metrics. This is essential for building targeted PromQL queries during investigation.

Examples: - Use when: "What jobs does Prometheus scrape?" → label='job'; read the values list. - Use when: "What instances are in the 'node-exporter' job?" → label='instance', match='{job="node-exporter"}'. - Use when: "What namespaces have metrics?" → label='namespace'. - Don't use when: You want metric names (call prometheus_list_metrics — has substring filtering). - Don't use when: You want current metric values (call prometheus_query with a PromQL expression).

Returns: dict with label / match / total_count / returned_count / truncated / values (sorted list).

List recording and alerting rules from Prometheus.

Wraps GET /api/v1/rules. Returns rule groups with their rules, including the PromQL expression, rule type (recording or alerting), and for alerting rules their current state (firing/pending/inactive).

Use this to understand the alerting configuration, find recording rules that pre-compute useful aggregations, and investigate which rules are currently firing or have health issues.

Examples: - Use when: "What alerting rules are configured?" → type='alert'; inspect rule names and expressions. - Use when: "Are there any recording rules I can use instead of computing aggregations from scratch?" → type='record'; look for rules matching your investigation. - Use when: "Why is this alert firing? What's its PromQL expression?" → call with no filter; find the alert by name; read its query. - Don't use when: You want to see which alerts are currently firing (call prometheus_list_alerts — shows active alerts with state and value, without the PromQL definition).

Returns: dict with type_filter / total_groups / total_rules / recording_count / alerting_count / groups (list of rule groups with name, file, rule_count, rules).

List all silences from Alertmanager.

Wraps GET /api/v2/silences. Returns silences with matchers, status (active/pending/expired), creator, comment, and time bounds.

Use this to understand which alerts are currently silenced and why. During incident handoffs, knowing what's silenced is critical — a silenced alert is invisible in Prometheus /alerts.

Examples: - Use when: "Is the HighCPU alert silenced?" → search silences for matching matchers. - Use when: "Who silenced alerts for the payment service?" → check createdBy and comment. - Don't use when: You want active firing alerts (call alertmanager_list_alerts).

Returns: dict with total_count / active_count / pending_count / expired_count / silences (list with matchers, status, etc.).

List alerts from Alertmanager with suppression state.

Wraps GET /api/v2/alerts. Returns alerts with their status (active/suppressed/unprocessed), silence IDs, and inhibition IDs.

Unlike prometheus_list_alerts, this shows WHY an alert is or isn't firing — suppressed alerts include silencedBy and inhibitedBy arrays.

Examples: - Use when: "Why isn't the HighCPU alert firing?" → check if it's suppressed (silencedBy or inhibitedBy). - Use when: "Show all suppressed alerts" → filter by status.state == 'suppressed'. - Don't use when: You want Prometheus-side alert state (call prometheus_list_alerts).

Returns: dict with total_count / active_count / suppressed_count / unprocessed_count / alerts (list with status, silencedBy, etc.).

Get Alertmanager cluster status, version, and config.

Wraps GET /api/v2/status. Returns cluster state (ready/settling), version info, uptime, and the raw configuration YAML.

Examples: - Use when: "Is Alertmanager healthy?" → check cluster_status. - Use when: "What version of Alertmanager is running?" → check version_info. - Don't use when: You want to see active alerts (call alertmanager_list_alerts).

Returns: dict with cluster_status / version_info / uptime / config_yaml.

List alert groups from Alertmanager showing routing topology.

Wraps GET /api/v2/alerts/groups. Returns groups with their labels, receiver, and alert count — shows how alerts are grouped for notification.

Examples: - Use when: "Why did I get one notification instead of many?" → check which alerts are in the same group. - Use when: "What receiver handles payment alerts?" → find the group and check its receiver. - Don't use when: You want individual alert details (call alertmanager_list_alerts).

Returns: dict with total_groups / total_alerts / groups (list with labels, receiver, alert_count).

Correlate alerts across multiple Prometheus instances.

Identifies related alerts that fire simultaneously or in sequence across different Prometheus instances using temporal windows and label similarity.

Use this to:

• Understand cross-instance incident scope

• Identify related alerts in different clusters/regions

• Detect systemic issues affecting multiple instances

Examples: - "Are there related alerts firing across our US and EU clusters?" - "Show me alerts that might be related to this HighCPU alert"

Returns: CorrelationResult with correlated alerts, groups, and cascades.

Group alerts by service identifiers across all instances.

Clusters related alerts into service-level incident analysis bundles.

Use this to:

• Understand which services are affected by current incidents

• Focus incident response efforts on specific service teams

• Identify services with multiple simultaneous alerts

Examples: - "Which services are currently experiencing alerts?" - "Group all alerts by service for my incident report"

Returns: AlertGroupResult with alerts grouped by service identifier.

Detect cascading alert patterns with directional dependency inference.

Identifies alert propagation patterns that indicate dependency failures.

Use this to:

• Trace failure propagation paths through your system

• Identify root cause candidates for complex incidents

• Understand service dependency relationships

Examples: - "What alerts typically fire after DatabaseConnectionFailed?" - "Show me the failure propagation chain in this incident"

Returns: CascadeDetectionResult with detected cascades and root causes.

List all configured Prometheus and Alertmanager instances with health status

Check Prometheus liveness and readiness.

Calls GET /-/healthy and GET /-/ready — management endpoints outside the /api/v1 namespace. Returns whether each probe returned a 200 status code.

Use this to verify Prometheus is actually running before investigating blank query results. A failed health check means Prometheus is down; a failed readiness check means it's starting up or shutting down.

Examples: - Use when: "Why are all my queries returning empty results?" → check if Prometheus is healthy first. - Use when: Setting up a new MCP connection — verify the target is reachable and healthy. - Don't use when: You want metric values (call prometheus_query).

Returns: dict with healthy (bool), healthy_status_code, ready (bool), ready_status_code.

Get TSDB statistics and cardinality data from Prometheus.

Wraps GET /api/v1/status/tsdb. Returns head stats (total series, chunks, time range) and top-N lists: metrics by series count, labels by value count, and labels by memory usage.

Use this to investigate cardinality explosions — the #1 operational Prometheus problem. High series counts slow queries and increase memory.

Examples: - Use when: "Why is Prometheus using so much memory?" → check num_series and top_metrics_by_series. - Use when: "Which labels have the most values?" → check top_labels_by_value_count. - Don't use when: You want current metric values (call prometheus_query).

Returns: dict with num_series / chunk_count / min_time / max_time / top_metrics_by_series / top_labels_by_value_count / top_labels_by_memory_bytes.

Get Prometheus runtime information.

Wraps GET /api/v1/status/runtimeinfo. Returns operational data: goroutine count, time series count, storage retention policy, start time, corruption count, and config reload status.

Examples: - Use when: "Why is Prometheus slow?" → check goroutine count and time series count. - Use when: "What's the retention policy?" → check storage_retention. - Don't use when: You want the Prometheus version (call prometheus_get_build_info).

Returns: dict with start_time / goroutine_count / time_series_count / storage_retention / corruptionCount / reloadConfigSuccess / lastConfigTime.

Get Prometheus build information.

Wraps GET /api/v1/status/buildinfo. Returns version, Go version, Git revision, branch, build user, and build date.

Examples: - Use when: "What version of Prometheus is running?" → check version. - Use when: Debugging version-specific behavior. - Don't use when: You want runtime stats (call prometheus_get_runtime_info).

Returns: dict with version / revision / branch / buildUser / buildDate / goVersion.