# Infrahub Analyst

> Analyze and correlate Infrahub data using the MCP server. Use when querying live infrastructure data to answer operational questions, detect drift, correlate node types, investigate service impact, check maintenance windows, or produce ad-hoc reports — without writing pipeline code.

- Skill: `opsmill/infrahub-analyst` (Agent Skill, multi-file: 9 files)
- Install (CLI): `npx skillmds@latest add opsmill/infrahub-analyst`
- Raw SKILL.md: https://api.skillmd.com/api/skills/opsmill/infrahub-analyst/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: DevOps & Infra
- Author: opsmill (https://skillmd.com/u/opsmill)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/opsmill/infrahub-analyst

---


## Overview

Expert guidance for interactive data analysis
against a live Infrahub instance. This skill uses
the **Infrahub MCP server** to query, correlate,
and reason over infrastructure data on demand —
answering operational questions that span multiple
node types and relationships.

Use this skill for any question of the form
*"what does Infrahub currently know about X,
and how does it relate to Y?"*

Typical question patterns:

- **Compliance** — "Are all devices following
  the naming convention?"
- **Service impact** — "Which services are hosted
  on devices in this rack?"
- **Maintenance windows** — "Which devices are
  currently in a maintenance window, and what
  depends on them?"
- **Drift detection** — "Which realized devices
  differ from their topology design?"
- **Capacity** — "Which racks are over 80% full?"
- **Change impact** — "What BGP sessions, services,
  and IPs depend on this prefix?"
- **Inventory gaps** — "Which devices have no
  platform or OS version recorded?"

For **automated, pipeline-enforced** checks that
block proposed changes, see
`../infrahub-check-creator/SKILL.md`.
For **repeatable scheduled reports** exported as
artifacts, see `../infrahub-transform-creator/SKILL.md`.

## When to Use

- Answering operational questions interactively
  via natural language
- Cross-referencing two or more node types to find
  relationships or gaps
- Investigating the blast radius of a change before
  executing it
- Auditing data quality across the inventory
- Producing one-time or on-demand reports for
  stakeholders
- Exploring schema structure and data before writing
  a generator or check

## How It Works

The Infrahub MCP server exposes tools that let
Claude query Infrahub data directly.
The typical workflow:

1. **Query** — use MCP tools to fetch current state
   from Infrahub
2. **Correlate** — join, diff, or filter the data
   against a policy or second dataset
3. **Reason** — identify gaps, anomalies, or
   relationships
4. **Report** — surface findings with context and
   remediation hints

## Rule Categories

| Priority | Category | Prefix | Description |
| -------- | -------- | ------ | ----------- |
| CRITICAL | MCP Tools | `mcp-` | Available Infrahub MCP tools, invocation patterns, response structure |
| CRITICAL | Query Patterns | `query-` | GraphQL structures for fetching, filtering, and traversing relationships |
| HIGH | Correlation | `correlation-` | Joining, diffing, and reasoning over data from multiple queries |
| HIGH | Reporting Output | `reporting-` | Presenting findings: summaries, tables, per-object detail, remediation hints |
| MEDIUM | Approach Selection | `approach-` | When to use MCP analysis vs InfrahubCheck vs Transform |

## MCP Server Basics

When the Infrahub MCP server is connected, Claude
can call tools such as:

- **`mcp__infrahub__infrahub_query`** — Execute a
  GraphQL query (primary tool)
- **`mcp__infrahub__infrahub_list_schema`** — List
  available node kinds
- **`mcp__infrahub__infrahub_get`** — Retrieve a
  specific object by ID or filters
- **`mcp__infrahub__infrahub_create`** — Create an
  object (remediation, on a branch)
- **`mcp__infrahub__infrahub_update`** — Update an
  object (remediation, on a branch)

```graphql
# Example: find all devices in an active
# maintenance window
query MaintenanceDevices {
  MaintenanceWindow(status__value: "active") {
    edges {
      node {
        name { value }
        start_time { value }
        end_time { value }
        devices {
          edges {
            node {
              name { value }
              role { value }
              site {
                node { name { value } }
              }
            }
          }
        }
      }
    }
  }
}
```

## Typical Analysis Workflow

```text
1. Understand the question
   → "Which services depend on devices currently
      in a maintenance window?"

2. Identify the node types involved
   → MaintenanceWindow, DcimDevice, Service
     (or equivalent in your schema)

3. Query current state
   → mcp__infrahub__infrahub_query — one query
     per node type, or combined

4. Correlate the data
   → Join across node types, filter, count, diff

5. Report findings
   → Summarize with counts, list affected objects,
     suggest next steps
```

## Supporting References

- **[examples.md](./examples.md)** — Analysis
  patterns (naming, VLAN, BGP, maintenance,
  service impact)
- **[../infrahub-common/graphql-queries.md](../infrahub-common/graphql-queries.md)**
  — GraphQL query writing reference
- **[../infrahub-common/infrahub-yml-reference.md](../infrahub-common/infrahub-yml-reference.md)**
  — .infrahub.yml project configuration
- **[../infrahub-check-creator/SKILL.md](../infrahub-check-creator/SKILL.md)**
  — Automated pipeline checks (for enforcement)
- **[../infrahub-transform-creator/SKILL.md](../infrahub-transform-creator/SKILL.md)**
  — Transforms for scheduled report artifacts
- **[rules/](./rules/)** — Individual rules organized
  by category prefix