mcp-engine-public MCP — Casos de uso, Instalar & Demo en vivo

Por qué usarlo

Características clave

Reads Power BI tabular model structure (tables, columns, measures, relationships)
Runs DAX queries against the open model
Creates and modifies DAX measures
Manages relationships between tables
Local-only execution — no data leaves the machine

Demo en vivo

Cómo se ve en la práctica

engine-public.replay ▶ listo

0/0

Instalar

Elige tu cliente

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

{
  "mcpServers": {
    "engine-public": {
      "command": "TODO",
      "args": [
        "See README: https://github.com/maxanatsko/mcp-engine-public"
      ],
      "_inferred": true
    }
  }
}

Abre Claude Desktop → Settings → Developer → Edit Config. Reinicia después de guardar.

~/.cursor/mcp.json · .cursor/mcp.json

{
  "mcpServers": {
    "engine-public": {
      "command": "TODO",
      "args": [
        "See README: https://github.com/maxanatsko/mcp-engine-public"
      ],
      "_inferred": true
    }
  }
}

Cursor usa el mismo esquema mcpServers que Claude Desktop. La configuración del proyecto prevalece sobre la global.

VS Code → Cline → MCP Servers → Edit

{
  "mcpServers": {
    "engine-public": {
      "command": "TODO",
      "args": [
        "See README: https://github.com/maxanatsko/mcp-engine-public"
      ],
      "_inferred": true
    }
  }
}

Haz clic en el icono MCP Servers de la barra lateral de Cline y luego en "Edit Configuration".

~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "engine-public": {
      "command": "TODO",
      "args": [
        "See README: https://github.com/maxanatsko/mcp-engine-public"
      ],
      "_inferred": true
    }
  }
}

Mismo formato que Claude Desktop. Reinicia Windsurf para aplicar.

~/.continue/config.json

{
  "mcpServers": [
    {
      "name": "engine-public",
      "command": "TODO",
      "args": [
        "See README: https://github.com/maxanatsko/mcp-engine-public"
      ]
    }
  ]
}

Continue usa un array de objetos de servidor en lugar de un mapa.

~/.config/zed/settings.json

{
  "context_servers": {
    "engine-public": {
      "command": {
        "path": "TODO",
        "args": [
          "See README: https://github.com/maxanatsko/mcp-engine-public"
        ]
      }
    }
  }
}

Añádelo a context_servers. Zed recarga en caliente al guardar.

claude mcp add engine-public -- TODO 'See README: https://github.com/maxanatsko/mcp-engine-public'

Un solo comando. Verifica con claude mcp list. Quita con claude mcp remove.

Casos de uso

Usos del mundo real: mcp-engine-public

Write DAX without memorizing syntax

👤 Power BI analysts new to DAX ⏱ ~15 min intermediate

Cuándo usarlo: You know what you want in English; you don't want to debug CALCULATE for an hour.

Requisitos previos

Power BI Desktop with a model open — Launch Power BI Desktop and open your .pbix
MCP Engine installed and connected — See mcpengine.dev — installer under 5 min

Flujo

Orient the model

List the tables in the open model and key measures.✓ Copiado

→ Model map
Write the measure

Create a DAX measure 'YoY Revenue' that returns current revenue minus same period prior year, using Date[Date] for time intelligence.✓ Copiado

→ DAX + creation confirmation
Validate

Run the measure over 2024 vs 2025 and spot-check 3 rows.✓ Copiado

→ Numbers that look right

Resultado: A working measure with validation, not a guess.

Errores comunes

Time intelligence requires a properly marked date table — Verify Date table is marked as a date table first
Model calculations differ between DirectQuery and Import — Be aware of your storage mode; DirectQuery imposes DAX restrictions

Auto-document an existing Power BI model

👤 Analysts inheriting a .pbix ⏱ ~25 min beginner

Cuándo usarlo: The original author is gone and the model has 40 tables of mystery.

Flujo

Dump structure

Dump the model: every table's role, every measure's DAX, every relationship.✓ Copiado

→ Full structural listing
Write prose docs

Write a one-page explanation of this model for a new analyst: what it reports on, main tables, key measures.✓ Copiado

→ Human-readable model doc

Resultado: Useful documentation without reading every measure yourself.

Combinar con: filesystem

Refactor measures to follow naming + modeling conventions

👤 Teams standardizing Power BI practices ⏱ ~30 min intermediate

Cuándo usarlo: Measures are named inconsistently (e.g. 'Total Sales' vs 'SumSales').

Flujo

Find violations

List measures that don't follow the naming convention '<Verb> <Subject> [<Modifier>]'.✓ Copiado

→ Violation list
Rename safely

Propose renames; list any visuals or calculated tables that reference each old name.✓ Copiado

→ Rename plan with dependencies

Resultado: A consistent measure catalog with broken references caught before you hit Apply.

Combinaciones

Combínalo con otros MCPs para multiplicar por 10

engine-public + filesystem

Export model documentation as a Markdown file alongside the .pbix

Document the model and save as ~/Docs/PBI/sales-model.md next to sales.pbix.✓ Copiado

engine-public + postgres

Cross-check PBI measures against raw Postgres queries

PBI says Q1 revenue is $4.2M. Run the same query on the source Postgres DB and tell me if there's a discrepancy.✓ Copiado

Herramientas

Lo que expone este MCP

Herramienta	Entradas	Cuándo llamar	Coste
get_model_structure	(none)	Session start	free (local)
run_dax	query: str	Ad-hoc DAX query	free (local)
create_measure	table, name, expression	Add new measure	free (write)
update_measure	table, name, expression	Modify existing	free (write)
manage_relationship	from_table, from_col, to_table, to_col, action: create\|delete\|update	Schema changes	free (write)

Coste y límites

Lo que cuesta ejecutarlo

Cuota de API: None — local only
Tokens por llamada: Model dumps can be large; focus queries
Monetario: Proprietary license with permitted personal + commercial use (see mcpengine.dev/license)
Consejo: Ask for specific tables rather than a full model dump on complex reports.

Seguridad

Permisos, secretos, alcance

Almacenamiento de credenciales: None required — uses PBI Desktop's session

Salida de datos: Zero telemetry claimed; all local to PBI Desktop

Proprietary license — review terms at mcpengine.dev/license before enterprise use.
Changes write directly to the open model — save your .pbix before risky refactors.

Resolución de problemas

Errores comunes y soluciones

No Power BI instance found

Ensure Power BI Desktop is running with a report open; the MCP connects to the local port it exposes.

Verificar: Check Task Manager for msmdsrv process

DAX error: Column not found

Table/column reference is case-sensitive and must match exactly. Use the model structure dump to get names right.

Verificar: get_model_structure

Changes don't persist after closing PBI

PBI Desktop doesn't auto-save — Ctrl+S after each batch of changes.

Verificar: Title bar shows no asterisk

Alternativas

mcp-engine-public vs otros

Alternativa	Cuándo usarla	Contrapartida
Tabular Editor 3 (scripting)	You want a full scripting environment for PBI/SSAS models	Paid; no MCP surface
DAX Studio	You only need a DAX query tool	No write operations; no AI layer

Más

Recursos

📖 Lee el README oficial en GitHub

🐙 Ver issues abiertas

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