ms-ai-architect/skills/ms-ai-advisor/references/architecture/recommended-mcp-servers.md
Kjell Tore Guttormsen 3a73eeafdc refactor(ms-ai-architect): R13 del 1 — nøytraliser Cosmo-personaen i ref-korpusets headinger, etter å ha rettet en gate som var målt usann to ganger
Ordre 20260912T193441Z-7358817909. Steg 1 var ikke transformen, men å rette
roadmapens R13-gate og få den ratifisert. Gaten `grep -rl "Cosmo"
skills/*/references -> 0` var usann på to uavhengige måter:

1. Ordren fanget den første: 451 av forekomstene er Azure Cosmos DB, ekte
   produktinnhold. Diskriminatoren er ikke bokstaven «s» — `Cosmos <norsk
   substantiv>` er genitiv av personaen (`### Cosmos tonalitet`), mens
   `Cosmos DB`/`CosmosClient`/`cosmos_ru` er produkt.
2. Denne økten fant den andre: 132 persona-forekomster ligger i prosa,
   tabeller, dialog-replikker og proveniens-linjer. Heading-nøytralisering
   kan ikke nå dem, så «0 persona» er uoppnåelig også under den ratifiserte
   formen. Operatøren ratifiserte alternativ A: gaten speiler formen, og de
   132 bokføres til R13b/R14.

Tre korreksjoner av premisser som sto i ordren og STATE:
  «ca 320 produkt»   -> 451 (case-sensitivt nett manglet 327 lowercase
                        TOC-ankre + 99 identifikatorer; sann nevner 1 638)
  «169 headinger»    -> 401. 169 var `^## For Cosmo`-prefikset (168) og var
                        internt inkonsistent med sin egen topp-variant (204)
  «417 matcher ingen
   populasjon»       -> 417 er cosmo-headinger utenfor kodefences; briefens
                        nevner var reell hele tiden

Fence-bevissthet er målt skadelig, ikke nødvendig: begge toggle-regler er
gale på dette korpuset (naiv toggle skjuler en ekte heading i
chain-of-thought-prompting.md, CommonMark-regelen ubalanserer
service-level-documentation-dr.md). Fence-agnostisk deteksjon finner 401
heading-linjer i nøyaktig de samme 40 variantene som fence-bevisst finner
400 i — ingen kodeblokk-linje er byte-identisk til en persona-heading. Derfor
nøkles transformen på 40 enumererte heading-tekster og ignorerer fences. En
ukjent variant kaster; en slug-kollisjon kaster. Ingenting auto-fikses.

TOC-en regenereres ikke, den rettes kirurgisk: alle 327 persona-lenker hadde
lenketekst lik én av de 40 heading-tekstene og anker lik slugify av den
(327/327, 0 avvik), så heading og TOC-entry skrives i samme operasjon og
ingen mellomtilstand etterlater en død lenke.

Ratifisert målform: `For Cosmo`, `For Cosmo Skyberg` og `For arkitekten
(Cosmo)` konvergerer på `For arkitekten`. To filer kolliderte og er adjudisert
ved å lese dem, ikke ved regel.

Verifisering (alle 7 kriterier fra ordren):
  G1 persona på heading-linjer   401 -> 0
  G2 døde fragmentlenker         1 -> 1 (pre-eksisterende, unntatt)
  G3 produkt-forekomster         451 -> 451; `Cosmos DB|Azure Cosmos` 308 = 308
  de 3 kun-produkt-filene        byte-identiske
  nettet validert begge veier    injisert persona feller G1; genitiv feller G1;
                                 produkt-heading og de 3 filene passerer
  hele diffen                    802 heading-linjer + 654 TOC-linjer, ANNET = 0
  linjeantall                    728 lagt til = 728 slettet
  suite                          1120/1120 (1097 + 23 nye)
  validate-plugin                250 PASS / 0 FAIL
  stikkprøve                     10 filer, alle 5 skills, inkl. de 3 mest
                                 produkt-tunge (26/20/19) — kun heading+TOC

Utenfor scope, urørt: de 4 SKILL.md, de 23 commands, CLAUDE.md, README.md,
NOTICE.md, docs/ (alt R14).

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-09-12 22:12:28 +02:00

7.8 KiB

Recommended MCP Servers for AI Architect

Last updated: 2026-02 Status: Advisory Category: Architecture


Introduksjon

MCP (Model Context Protocol) servers extend the AI Architect plugin by providing real-time access to external tools and data sources. Rather than relying solely on static knowledge base files, MCP servers let the architect agent query live documentation, manage infrastructure, generate diagrams, and interact with project management systems directly during a session.

This reference documents which MCP servers are already integrated, which are recommended for enhanced functionality, and how they map to the architect workflow phases.


Allerede integrert

Server Formål Tools Workflow Phase
microsoft-learn Offisiell Microsoft dokumentasjon microsoft_docs_search, microsoft_docs_fetch, microsoft_code_sample_search Knowledge Validation (Phase 4-5)
mcp-image Bildegenerering med Imagen 3 generate_image Visualization (Phase 7)

microsoft-learn

Primary knowledge validation tool. Used by the research-agent to fetch latest platform capabilities, pricing, regional availability, and best practices. Critical for ensuring recommendations are current.

Typical usage in architect workflow:

  • Verify service availability in Norway East/West regions
  • Check latest SDK versions and deprecation notices
  • Validate security configuration recommendations
  • Fetch code samples for POC plans

mcp-image

Used by the diagram-generation-agent to create architecture diagrams via Imagen 3. Produces visual representations of proposed architectures for documentation and stakeholder communication.


Anbefalte tillegg

Azure MCP Server (microsoft/azure-mcp-server)

Description: Official Microsoft MCP server for Azure resource management. Provides read/write access to Azure subscriptions, resource groups, and individual services.

Key tools:

  • Resource group listing and management
  • Service configuration inspection
  • Deployment status checking
  • Cost and usage data retrieval

Use cases for architect:

  • Validate existing infrastructure before proposing changes
  • Check current SKUs and configuration for cost optimization reviews
  • Verify network topology and security group rules during security assessments
  • Inspect AI service deployments (Azure OpenAI endpoints, AI Search indexes)
  • Compare proposed architecture against actual deployed state

Relevant commands: /architect:security, /architect:cost, /architect:review

Installation:

{
  "mcpServers": {
    "azure": {
      "command": "npx",
      "args": ["-y", "@azure/mcp-server"],
      "env": {
        "AZURE_SUBSCRIPTION_ID": "<your-subscription-id>"
      }
    }
  }
}

Bicep MCP Server

Description: Infrastructure as Code generation and validation for Azure using Bicep templates. Translates architecture decisions into deployable infrastructure definitions.

Key tools:

  • Bicep template generation from natural language
  • Template validation and what-if analysis
  • Parameter file generation
  • Module composition

Use cases for architect:

  • Generate IaC templates from ADR decisions (/architect:adr output)
  • Validate proposed infrastructure is deployable
  • Create POC infrastructure templates (/architect:poc output)
  • Ensure compliance with Azure Policy through template validation
  • Generate migration scripts for /architect:migrate plans

Relevant commands: /architect:adr, /architect:poc, /architect:migrate

Installation:

{
  "mcpServers": {
    "bicep": {
      "command": "npx",
      "args": ["-y", "@azure/bicep-mcp-server"]
    }
  }
}

Azure DevOps MCP Server (microsoft/azure-devops-mcp)

Description: Integration with Azure DevOps for work items, pipelines, repositories, and boards. Bridges architecture decisions with implementation tracking.

Key tools:

  • Work item creation and querying
  • Pipeline status and trigger
  • Repository browsing
  • Board and sprint management

Use cases for architect:

  • Create implementation work items from architecture review findings
  • Track ADR implementation progress
  • Link POC plans to sprint backlogs
  • Monitor deployment pipeline status for migration plans
  • Query existing codebase for integration point analysis

Relevant commands: /architect:review, /architect:poc, /architect:migrate

Installation:

{
  "mcpServers": {
    "azure-devops": {
      "command": "npx",
      "args": ["-y", "@microsoft/azure-devops-mcp"],
      "env": {
        "AZURE_DEVOPS_ORG": "<your-org>",
        "AZURE_DEVOPS_PAT": "<your-pat>"
      }
    }
  }
}

Playwright MCP Server

Description: Browser automation for visual testing and verification. Enables the architect plugin to visually verify deployed solutions and capture screenshots.

Key tools:

  • Page navigation and screenshot capture
  • Element interaction and form filling
  • Visual regression comparison
  • Network request interception

Use cases for architect:

  • Visual verification of diagram-generation-agent output
  • Screenshot capture of Azure Portal configurations during reviews
  • Validate Copilot Studio agent behavior in browser
  • Capture evidence for architecture review documentation
  • Accessibility testing (WCAG compliance checks)

Relevant commands: /architect:diagram, /architect:review

Installation:

{
  "mcpServers": {
    "playwright": {
      "command": "npx",
      "args": ["-y", "@anthropic/mcp-playwright"]
    }
  }
}

MCP Server Selection Matrix

Workflow Need Primary MCP Fallback
Documentation lookup microsoft-learn WebSearch
Resource inspection azure Azure Portal (manual)
IaC generation bicep Manual Bicep authoring
Work item tracking azure-devops Linear (already configured)
Visual verification playwright Manual screenshot
Diagram generation mcp-image Mermaid in markdown

Installasjon

Add MCP servers to your Claude Code settings file at ~/.claude/settings.json or project-level .claude/settings.json:

{
  "mcpServers": {
    "microsoft-learn": {
      "command": "npx",
      "args": ["-y", "@anthropic/mcp-microsoft-learn"]
    },
    "azure": {
      "command": "npx",
      "args": ["-y", "@azure/mcp-server"],
      "env": {
        "AZURE_SUBSCRIPTION_ID": "<sub-id>"
      }
    },
    "bicep": {
      "command": "npx",
      "args": ["-y", "@azure/bicep-mcp-server"]
    }
  }
}

Notes:

  • MCP servers requiring authentication (Azure, Azure DevOps) need environment variables configured
  • Use .env files or secret managers -- never commit credentials
  • Test each server independently before combining
  • Monitor MCP server resource usage in long sessions

For arkitekten

These MCP servers enhance the 7-phase architect workflow:

Phase MCP Enhancement
1. Problem Understanding azure-devops: Query existing work items and requirements
2. Context & Constraints azure: Inspect current infrastructure state
3. Capacity & Ambition azure: Check subscription limits and quotas
4. Knowledge Validation microsoft-learn: Verify latest documentation
5. Knowledge Integration microsoft-learn + azure: Combine docs with live state
6. Architecture Proposal bicep: Generate deployable IaC from proposal
7. Visualization mcp-image: Generate architecture diagrams

Priority order for adoption:

  1. microsoft-learn (already integrated, essential)
  2. mcp-image (already integrated, visualization)
  3. azure (highest value-add for live infrastructure validation)
  4. bicep (IaC generation from architecture decisions)
  5. azure-devops (implementation tracking bridge)
  6. playwright (visual verification, nice-to-have)