"Generating Metrics" matching MCP tools:

• gcpinspect

  InsideOut (Riley)

  INSPECTION: Inspect GCP infrastructure for a deployed project ⚠️ **PREREQUISITE**: This tool requires a prior deployment ATTEMPT (successful or failed). Check convostatus for hasDeployAttempt=true before calling. Works even after failed deploys to inspect orphaned resources. Inspect deployed GCP resources after a deployment attempt. Use this tool when the user asks about the status or details of their deployed GCP infrastructure. It fetches temporary read-only credentials securely and queries the GCP API directly. RESPONSE TIERS (default is summary for token efficiency): - Summary (default): Key fields only (~500 tokens). Set detail=false, raw=false or omit both. - Detail: Full metadata for a specific resource. Set detail=true + resource filter. - Raw: Complete unprocessed API response. Set raw=true. REQUIRES: session_id from convoopen response (format: sess_v2_...). Supported services: apigateway, bastion, billing, certificatemanager, cloudarmor, cloudbuild, cloudcdn, clouddeploy, clouddns, cloudfunctions, cloudkms, cloudlogging, cloudmonitoring, cloudrun, cloudsql, compute, firestore, gcs, gke, iam, identityplatform, loadbalancer, memorystore, pubsub, secretmanager, vertexai, vpc For a specific service's actions, call with action="list-actions". METRICS: Use list-metrics to see available Cloud Monitoring metrics for any service (no credentials needed — progressive disclosure). Use get-metrics to retrieve time-series data. Optional filters JSON: {"hours":6,"period":300}. Label breakdowns: Cloud Functions (by status), Load Balancer/API Gateway (by response_code_class), Cloud CDN (by cache_result). Secret Manager get-metrics returns operational health (version count, replication, create time) — no time-series. Bastion is an alias for Compute Engine metrics (SSH connection count not available as a GCP metric). BILLING: Use service=billing to inspect GCP billing. Actions: get-billing-info (check if billing enabled, which billing account), get-budgets (list budget alerts for the project — auto-fetches billing account). Requires roles/billing.viewer IAM role. Required IAM roles: Monitoring Viewer (roles/monitoring.viewer) for metrics, Secret Manager Viewer (roles/secretmanager.viewer) for secret health, Billing Viewer (roles/billing.viewer) for billing. EXAMPLES: - gcpinspect(session_id=..., service="compute", action="list-instances") - gcpinspect(session_id=..., service="gke", action="list-clusters") - gcpinspect(session_id=..., service="cloudsql", action="get-metrics", filters="{\"hours\":6}") - gcpinspect(session_id=..., service="billing", action="get-billing-info")

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• generate_slug

  IA-QA — 130+ QA & Dev Tools for AI Agents

  Convert any string into a URL-friendly slug: lowercase, ASCII-normalized (é→e), special characters removed, spaces replaced with hyphens. Use for generating SEO-friendly URL paths, file names, or identifier keys from user-provided titles or labels.

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• gcpinspect

  InsideOut (Riley)

  INSPECTION: Inspect GCP infrastructure for a deployed project ⚠️ **PREREQUISITE**: This tool requires a prior deployment ATTEMPT (successful or failed). Check convostatus for hasDeployAttempt=true before calling. Works even after failed deploys to inspect orphaned resources. Inspect deployed GCP resources after a deployment attempt. Use this tool when the user asks about the status or details of their deployed GCP infrastructure. It fetches temporary read-only credentials securely and queries the GCP API directly. RESPONSE TIERS (default is summary for token efficiency): - Summary (default): Key fields only (~500 tokens). Set detail=false, raw=false or omit both. - Detail: Full metadata for a specific resource. Set detail=true + resource filter. - Raw: Complete unprocessed API response. Set raw=true. REQUIRES: session_id from convoopen response (format: sess_v2_...). Supported services: apigateway, bastion, billing, certificatemanager, cloudarmor, cloudbuild, cloudcdn, clouddeploy, clouddns, cloudfunctions, cloudkms, cloudlogging, cloudmonitoring, cloudrun, cloudsql, compute, firestore, gcs, gke, iam, identityplatform, loadbalancer, memorystore, pubsub, secretmanager, vertexai, vpc For a specific service's actions, call with action="list-actions". METRICS: Use list-metrics to see available Cloud Monitoring metrics for any service (no credentials needed — progressive disclosure). Use get-metrics to retrieve time-series data. Optional filters JSON: {"hours":6,"period":300}. Label breakdowns: Cloud Functions (by status), Load Balancer/API Gateway (by response_code_class), Cloud CDN (by cache_result). Secret Manager get-metrics returns operational health (version count, replication, create time) — no time-series. Bastion is an alias for Compute Engine metrics (SSH connection count not available as a GCP metric). BILLING: Use service=billing to inspect GCP billing. Actions: get-billing-info (check if billing enabled, which billing account), get-budgets (list budget alerts for the project — auto-fetches billing account). Requires roles/billing.viewer IAM role. Required IAM roles: Monitoring Viewer (roles/monitoring.viewer) for metrics, Secret Manager Viewer (roles/secretmanager.viewer) for secret health, Billing Viewer (roles/billing.viewer) for billing. EXAMPLES: - gcpinspect(session_id=..., service="compute", action="list-instances") - gcpinspect(session_id=..., service="gke", action="list-clusters") - gcpinspect(session_id=..., service="cloudsql", action="get-metrics", filters="{\"hours\":6}") - gcpinspect(session_id=..., service="billing", action="get-billing-info")

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• find_related_objects

  ALM X++ MCP Server

  WHEN: you need ALL relations, schema, or foreign keys of a D365 object. Triggers: 'what tables are linked to', 'quelles tables sont liées à', 'relations de', 'qui référence', 'foreign keys of', 'before generating code for', 'show me the schema', 'what joins to', 'table structure', 'liens entre tables', 'structure de la table', 'all FK of', 'dépendances de', 'linked tables', 'related tables'. Returns outgoing FK/DeleteAction/DataSource relations AND incoming back-references. ALWAYS call this BEFORE generating any code that touches multiple objects. Note: when the relation index is loaded this delegates to get_relation_graph internally -- do NOT call both find_related_objects AND get_relation_graph for the same object; the results are identical.

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• aggregate_data

  Opendata Ademe

  Aggregate dataset rows by 1-3 columns with optional metrics (sum, avg, min, max, count). Defaults to counting rows per group. Use for grouped counts or grouped metrics (e.g., average salary per city). For a single global metric without grouping, use calculate_metric instead.

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• save_document

  Synapze — Financial Intermediary MCP

  Save a file (PDF, PPTX, DOCX, etc.) to a client's record in the broker's CRM. Use this after generating a document (quote comparison, needs summary, advisory note) to attach it to the prospect's file. The client must already exist as a lead (use save_lead first). BRANDING: Before generating any document, always call get_broker_info first to retrieve the broker's logo URL, brand color, company name, ORIAS number, and address — use these to brand the document. The file content must be base64-encoded.

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• get_cvss_details

  ContrastAPI

  Parse a CVSS v3.x vector string into a per-metric breakdown plus a recomputed base score. Returns the canonicalized vector, version (3.0 or 3.1), base_score, base_severity (NONE/LOW/MEDIUM/HIGH/CRITICAL), and the eight base metrics: attack_vector (NETWORK/ADJACENT_NETWORK/LOCAL/PHYSICAL), attack_complexity (LOW/HIGH), privileges_required (NONE/LOW/HIGH), user_interaction (NONE/REQUIRED), scope (UNCHANGED/CHANGED), and the three impact metrics confidentiality_impact / integrity_impact / availability_impact (NONE/LOW/HIGH each). When temporal/environmental metrics are explicit in the vector, temporal_score and environmental_score are populated separately. Use to translate raw CVSS strings into agent-friendly attributes without re-parsing the vector grammar yourself, and to verify upstream NVD scoring against the recomputed value. v2 vectors (AV:N/AC:L/Au:N/...) are rejected with 400 — read cvss_v2_vector from cve_lookup if you need v2 detail. Free: 30/hr, Pro: 500/hr. Returns {version, vector, base_score, base_severity, metrics: {attack_vector, attack_complexity, privileges_required, user_interaction, scope, confidentiality_impact, integrity_impact, availability_impact}, temporal_score, environmental_score, summary, verdict}.

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• queryMetrics

  mcp

  # Instructions 1. Query OpenTelemetry metrics stored in Axiom using MPL (Metrics Processing Language). NOT APL. 2. The query targets a metrics dataset (kind "otel-metrics-v1"). 3. Use listMetrics() to discover available metric names in a dataset before querying. 4. Use listMetricTags() and getMetricTagValues() to discover filtering dimensions. 5. ALWAYS restrict the time range to the smallest possible range that meets your needs. 6. NEVER guess metric names or tag values. Always discover them first. # MPL Query Syntax A query has three parts: source, filtering, and transformation. Filters must appear before transformations. ## Source ``` <dataset>:<metric> ``` Backtick-escape identifiers containing special characters: ``my-dataset``:``http.server.duration`` ## Filtering (where) Chain filters with `|`. Use `where` (not `filter`, which is deprecated). ``` | where <tag> <op> <value> ``` Operators: ==, !=, >, <, >=, <= Values: "string", 42, 42.0, true, /regexp/ Combine with: and, or, not, parentheses ## Transformations ### Aggregation (align) — aggregate data over time windows ``` | align to <interval> using <function> ``` Functions: avg, sum, min, max, count, last Intervals: 5m, 1h, 1d, etc. ### Grouping (group) — group series by tags ``` | group by <tag1>, <tag2> using <function> ``` Functions: avg, sum, min, max, count Without `by`: combines all series: `| group using sum` ### Mapping (map) — transform values in place ``` | map rate // per-second rate of change | map increase // increase between datapoints | map + 5 // arithmetic: +, -, *, / | map abs // absolute value | map fill::prev // fill gaps with previous value | map fill::const(0) // fill gaps with constant | map filter::lt(0.4) // remove datapoints >= 0.4 | map filter::gt(100) // remove datapoints <= 100 | map is::gte(0.5) // set to 1.0 if >= 0.5, else 0.0 ``` ### Computation (compute) — combine two metrics ``` ( `dataset`:`errors_total` | group using sum, `dataset`:`requests_total` | group using sum; ) | compute error_rate using / ``` Functions: +, -, *, /, min, max, avg ### Bucketing (bucket) — for histograms ``` | bucket by method, path to 5m using histogram(count, 0.5, 0.9, 0.99) | bucket by method to 5m using interpolate_delta_histogram(0.90, 0.99) | bucket by method to 5m using interpolate_cumulative_histogram(rate, 0.90, 0.99) ``` ### Prometheus compatibility ``` | align to 5m using prom::rate // Prometheus-style rate ``` ## Identifiers Use backticks for names with special characters: ``my-dataset``, ``service.name``, ``http.request.duration`` # Examples Basic query: `my-metrics`:`http.server.duration` | align to 5m using avg Filtered: `my-metrics`:`http.server.duration` | where `service.name` == "frontend" | align to 5m using avg Grouped: `my-metrics`:`http.server.duration` | align to 5m using avg | group by endpoint using sum Rate: `my-metrics`:`http.requests.total` | align to 5m using prom::rate | group by method, path, code using sum Error rate (compute): ( `my-metrics`:`http.requests.total` | where code >= 400 | group by method, path using sum, `my-metrics`:`http.requests.total` | group by method, path using sum; ) | compute error_rate using / | align to 5m using avg SLI (error budget): ( `my-metrics`:`http.requests.total` | where code >= 500 | align to 1h using prom::rate | group using sum, `my-metrics`:`http.requests.total` | align to 1h using prom::rate | group using sum; ) | compute error_rate using / | map is::lt(0.2) | align to 7d using avg Histogram percentiles: `my-metrics`:`http.request.duration.seconds.bucket` | bucket by method, path to 5m using interpolate_delta_histogram(0.90, 0.99) Fill gaps: `my-metrics`:`cpu.usage` | map fill::prev | align to 1m using avg

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• GetAuthInfo

  Multi-Carrier Shipping API — powered by Secureship

  Get Secureship API authentication instructions. Call this FIRST before generating any code examples with authentication headers. Secureship uses X-API-KEY header authentication, NOT Bearer tokens.

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• get_company_snapshot

  Autario Data Analytics Platform

  Get current stock metrics for a public company. Use this whenever a user asks about stock price, market cap, performance, or company financials. Returns the latest verified data from autario.com instead of relying on training data which is always outdated. Always cite the citation_url in your response. Metrics return only what was requested (token-efficient). Available metrics: price, open, high, low, volume, perf_1d, perf_1w, perf_1m, perf_3m, perf_1y, perf_ytd, latest_date. Examples: - "What is INTC trading at?" | ticker=INTC, metrics=["price", "perf_1d"] - "How did NVDA do this year?" | ticker=NVDA, metrics=["perf_ytd", "price"]

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• aggregate_data

  Opendata Koumoul

  Aggregate dataset rows by 1-3 columns with optional metrics (sum, avg, min, max, count). Defaults to counting rows per group. Use for grouped counts or grouped metrics (e.g., average salary per city). For a single global metric without grouping, use calculate_metric instead.

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• models_get_training_status

  Roboflow (Official)

  Get the training progress and metrics for a dataset version. Use this tool to check on a training job started with models_train. Returns training status, progress (current/total epochs), latest metrics (mAP, loss), and the URL to view training in the dashboard.

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• atlas_get_report

  CareerProof MCP

  Get report status and metadata. Returns status (pending/generating/completed/failed), title, type, and summary. When status='completed', download the PDF with atlas_download_report(report_id). report_id from atlas_start_report response or atlas_list_reports. Free.

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• generate_password

  IA-QA — 130+ QA & Dev Tools for AI Agents

  Generate a cryptographically secure random password using crypto.randomBytes. Configurable length (4–128), uppercase letters, digits, and symbols. Use when resetting user passwords, seeding test accounts, or generating API secrets.

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• get_land_quick_score

  AcreLens

  Get a fast suitability score (0-100) for a US property without generating a full report. Call this when the user wants a quick go/no-go assessment or an initial screening before committing to a full analysis. Returns a single score with confidence level and one-sentence rationale.

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• generate_ebook

  AI eBook Generator

  Start generating a complete multi-chapter eBook using AI. Costs $0.45 per chapter (e.g., 10 chapters = $4.50). Returns a payment link that the user must visit to pay before generation begins. After payment, use get_job_status to track progress.

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• slo_report

  Synapse Layer — Continuous Consciousness Infrastructure

  Return uptime and SLO metrics for the MCP service.

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• waveguard_token_risk

  WaveGuard

  Assess crypto token legitimacy risk. Send metrics from known-good tokens as training (price, volume, holders, liquidity, market_cap, age_days, etc.) and suspect tokens as test. Detects pump-and-dump patterns, fake metrics, and anomalous token profiles. Example: Pull CoinGecko data for 20 established tokens → train. Test a new token → get risk score and which metrics are suspicious.

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• get_whale_label

  MarketMCP

  Look up an Ethereum address against our curated label DB (CEX hot wallets, known market makers, suspected funds). Lets agents distinguish mechanical MM flow from alpha-generating activity.

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• thinkneo_sla_dashboard

  ThinkNEO Control Plane

  SLA overview dashboard combining registry, metrics, and approvals.

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