InfraProfiler MCP

Infrastructure, cost, and pipeline intelligence

InfraProfiler MCP connects infrastructure telemetry and delivery data so teams can rank cost, reliability, saturation, and deployment bottlenecks.

Included with an active usage plan

Available through the hosted catalog. Calls count against the shared allowance on the account plan.

Compare usage plans

Why it exists

Connect infrastructure telemetry and pipeline data, then rank the bottlenecks that matter most.

Generic terminals, provider APIs, and custom prompts can cover parts of the work, but the caller must supply permission limits, output requirements, failure handling, and usage accounting.

Connection and contract

Connect from an MCP-aware client with an account-scoped Monarchic key. The hosted route checks access, runs the named product contract, and records the operation on the account receipt.

The product-specific schema defines the inputs and outputs used by clients and downstream automation.

Current limits

Live provider collection is a separate operation and requires a request-scoped read token. Savings are deterministic projections, not guarantees.

This call only reads the telemetry in the request. It needs no provider token, filesystem, subprocess, Kubernetes, or cloud mutation access.

What you get

Rank infrastructure and delivery hotspots
Trace cost, reliability, and latency signals
Export architecture graphs and optimization plans

Core use case

Connect infrastructure telemetry and pipeline data, then rank the bottlenecks that matter most.

Outcomes

Prioritize cost, reliability, saturation, and delivery hotspots
Connect pipeline behavior to runtime infrastructure and ownership
Produce architecture graphs and ranked optimization plans

Primary workflows

Hotspot ranking Cost analysis Pipeline profiling Architecture export

Concrete workflow / priced call

Find the bottleneck in a slow deployment pipeline

The request, exact tool-call payload, returned output, and usage receipt are shown below.

Request

“Why did this deployment take 15 minutes, and what should we fix first?”

Execution

Tool call payload

{
  "tool": "profile_pipeline",
  "arguments": {
    "run": {
      "id": "gha.acme.api.deploy.42",
      "provider": "github_actions",
      "repository": "acme/api",
      "workflow": "deploy",
      "branch": "main",
      "trigger": "push",
      "totalDurationSeconds": 900,
      "stages": [
        {
          "id": "queue",
          "name": "Queue",
          "durationSeconds": 0,
          "queueSeconds": 120
        },
        {
          "id": "install",
          "name": "Install",
          "durationSeconds": 360,
          "dependsOn": [
            "queue"
          ],
          "cache": {
            "key": "deps",
            "hit": false
          },
          "networkSeconds": 240
        },
        {
          "id": "unit",
          "name": "Unit tests",
          "durationSeconds": 240,
          "dependsOn": [
            "install"
          ]
        },
        {
          "id": "deploy",
          "name": "Deploy",
          "durationSeconds": 180,
          "dependsOn": [
            "unit"
          ]
        }
      ]
    }
  }
}

Builds the critical path from caller-supplied timings, identifies queue, cache, network, and stage bottlenecks, then projects bounded optimizations.

Output

Representative contract excerpt

{
  "run": {
    "id": "gha.acme.api.deploy.42",
    "provider": "github_actions",
    "repository": "acme/api",
    "workflow": "deploy"
  },
  "totalDurationSeconds": 900,
  "criticalPathSeconds": 900,
  "criticalPath": [
    {
      "id": "queue",
      "name": "Queue",
      "durationSeconds": 0,
      "queueSeconds": 120
    },
    {
      "id": "install",
      "name": "Install",
      "durationSeconds": 360,
      "networkSeconds": 240
    },
    {
      "id": "unit",
      "name": "Unit tests",
      "durationSeconds": 240
    },
    {
      "id": "deploy",
      "name": "Deploy",
      "durationSeconds": 180
    }
  ],
  "queueDelaySeconds": 120,
  "cacheMisses": 1,
  "networkSeconds": 240,
  "bottlenecks": [
    {
      "stageId": "install",
      "stageName": "Install",
      "category": "critical_path",
      "impactSeconds": 360,
      "evidence": "Install contributes 6m to the critical path"
    }
  ],
  "estimatedSavingsSeconds": 203,
  "optimizedDurationSeconds": 697,
  "optimizations": [
    {
      "title": "Stabilize dependency and Docker cache keys",
      "category": "cache",
      "estimatedSavingsSeconds": 113,
      "affectedStages": [
        "install"
      ]
    }
  ]
}

Usage rating

At runtime

Recorded on the operation receipt

The completed analysis receives a measured receipt. Allowance quantities remain unpublished until the fully allocated rate card is frozen.