DDC_Skills_for_AI_Agents_in_Construction MCP — Anwendungsfälle, Installieren & Live-Demo

Warum nutzen

Hauptfunktionen

Breadth: 221 sub-skills across the construction lifecycle
BIM data handling (IFC parsing, Revit exports, model audits)
Cost estimation templates and WBS conventions
Scheduling helpers (P6/MS Project-adjacent)
Document control: submittals, RFIs, change orders

Live-Demo

In der Praxis

ddc-skills-for-ai-agents-in-construction-skill.replay ▶ bereit

0/0

Installieren

Wählen Sie Ihren Client

~/Library/Application Support/Claude/claude_desktop_config.json · Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "ddc-skills-for-ai-agents-in-construction-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction",
        "~/.claude/skills/DDC_Skills_for_AI_Agents_in_Construction"
      ],
      "_inferred": true
    }
  }
}

Öffne Claude Desktop → Settings → Developer → Edit Config. Nach dem Speichern neu starten.

~/.cursor/mcp.json · .cursor/mcp.json

{
  "mcpServers": {
    "ddc-skills-for-ai-agents-in-construction-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction",
        "~/.claude/skills/DDC_Skills_for_AI_Agents_in_Construction"
      ],
      "_inferred": true
    }
  }
}

Cursor nutzt das gleiche mcpServers-Schema wie Claude Desktop. Projektkonfiguration schlägt die globale.

VS Code → Cline → MCP Servers → Edit

{
  "mcpServers": {
    "ddc-skills-for-ai-agents-in-construction-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction",
        "~/.claude/skills/DDC_Skills_for_AI_Agents_in_Construction"
      ],
      "_inferred": true
    }
  }
}

Klicken Sie auf das MCP-Servers-Symbol in der Cline-Seitenleiste, dann "Edit Configuration".

~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "ddc-skills-for-ai-agents-in-construction-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction",
        "~/.claude/skills/DDC_Skills_for_AI_Agents_in_Construction"
      ],
      "_inferred": true
    }
  }
}

Gleiche Struktur wie Claude Desktop. Windsurf neu starten zum Übernehmen.

~/.continue/config.json

{
  "mcpServers": [
    {
      "name": "ddc-skills-for-ai-agents-in-construction-skill",
      "command": "git",
      "args": [
        "clone",
        "https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction",
        "~/.claude/skills/DDC_Skills_for_AI_Agents_in_Construction"
      ]
    }
  ]
}

Continue nutzt ein Array von Serverobjekten statt einer Map.

~/.config/zed/settings.json

{
  "context_servers": {
    "ddc-skills-for-ai-agents-in-construction-skill": {
      "command": {
        "path": "git",
        "args": [
          "clone",
          "https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction",
          "~/.claude/skills/DDC_Skills_for_AI_Agents_in_Construction"
        ]
      }
    }
  }
}

In context_servers hinzufügen. Zed lädt beim Speichern neu.

claude mcp add ddc-skills-for-ai-agents-in-construction-skill -- git clone https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction ~/.claude/skills/DDC_Skills_for_AI_Agents_in_Construction

Einzeiler. Prüfen mit claude mcp list. Entfernen mit claude mcp remove.

Anwendungsfälle

Praxisnahe Nutzung: DDC_Skills_for_AI_Agents_in_Construction

How to audit a BIM IFC model for basic data quality

👤 BIM coordinators and VDC teams ⏱ ~60 min advanced

Wann einsetzen: You receive an IFC file from a consultant and need a quality check.

Voraussetzungen

Python with ifcopenshell — pip install ifcopenshell
Skill cloned — git clone https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction ~/.claude/skills/DDC_Skills_for_AI_Agents_in_Construction

Ablauf

Parse the IFC

Audit model.ifc — count entities by class, find missing Psets, flag orphan geometry.✓ Kopiert

→ Entity counts + quality flags
Check naming and classification

Verify wall and room naming against our company standard.✓ Kopiert

→ Per-element conformance report
Produce a coordinator-ready report

Generate an issue list the consultant can act on.✓ Kopiert

→ Ordered issue list

Ergebnis: A model audit report you can send back in under an hour.

Fallstricke

Huge IFC files exceed memory — Stream-parse rather than load full tree; or pre-filter by spatial structure

Kombinieren mit: filesystem

Produce a quick order-of-magnitude cost estimate

👤 Estimators, PMs, bid teams ⏱ ~30 min intermediate

Wann einsetzen: Early-phase numbers for a concept before you commit to a detailed estimate.

Ablauf

Describe the project

Concrete frame office, ~12,000 sqm, Tier-1 city, shell-only. Give me a per-sqm cost range.✓ Kopiert

→ Range with the assumptions stated
Break into WBS

Break the estimate into WBS sections with % allocations.✓ Kopiert

→ Top-level WBS with line items
Flag risks

List the top 5 cost risks for this concept.✓ Kopiert

→ Risks with impact

Ergebnis: A defensible concept estimate ready for internal review.

Fallstricke

Using global averages without local adjustment — Always override with local benchmarks when you have them

Review a construction schedule for common issues

👤 Schedulers and PMs ⏱ ~30 min intermediate

Wann einsetzen: You got a schedule from a subcontractor and need to check for the obvious red flags.

Ablauf

Feed the schedule

Review schedule.xlsx — flag missing logic, negative float, open ends, and unrealistic durations.✓ Kopiert

→ Categorized findings
Prioritize

Rank by impact on completion date.✓ Kopiert

→ Sorted list

Ergebnis: Quick surface-level schedule review that catches 80% of common problems.

Fallstricke

Missing CPM-level analysis — For real float analysis, export from P6 rather than relying on Excel

Kombinationen

Mit anderen MCPs für 10-fache Wirkung

ddc-skills-for-ai-agents-in-construction-skill + filesystem

Process a whole project folder of IFCs, schedules, and docs

Walk project/ and produce a weekly coordination packet.✓ Kopiert

Werkzeuge

Was dieses MCP bereitstellt

Werkzeug	Eingaben	Wann aufrufen	Kosten
bim-audit	IFC path	On any incoming IFC	ifcopenshell compute
cost-estimation	project concept	Early phase	0
schedule-review	schedule export	Sub-submittal review	0
document-control	RFIs/submittals/COs	Project admin	0

Kosten & Limits

Was der Betrieb kostet

API-Kontingent: none
Tokens pro Aufruf: 5–30k per task
Kosten in €: free at skill level
Tipp: Use only the sub-skills relevant to your role — this bundle is wide

Sicherheit

Rechte, Secrets, Reichweite

Credential-Speicherung: none

Datenabfluss: none

Construction estimates and schedules are often confidential — handle like other sensitive project data

Fehlerbehebung

Häufige Fehler und Lösungen

ifcopenshell install fails

Use Python 3.10 or 3.11 and pip install ifcopenshell from a wheel matching your platform.

Prüfen: python -c 'import ifcopenshell; print(ifcopenshell.version)'

Estimates are wildly off

Override unit costs with your regional database; the skill uses generic benchmarks only

Alternativen

DDC_Skills_for_AI_Agents_in_Construction vs. andere

Alternative	Wann stattdessen	Kompromiss
generic csv-data-summarizer-claude-skill	Your construction data is CSV and you don't need BIM semantics	No domain knowledge

Mehr

Ressourcen

📖 Offizielle README auf GitHub lesen

🐙 Offene Issues ansehen

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