# EraCore Revit MCP

> EraCore Revit MCP — soewal19-eracore-revit-mcp. Use this tool when you need to integrate Large Language Model (LLM) assistants with Autodesk Revit Building Information Modeling (BIM) models to automate tasks such as metadata reading, geometry creation, and batch parameter updates. It solves problems related to data extraction, model manipulation, and schedule export, providing a seamless interface between LLMs and Revit models. The EraCore Revit MCP tool accepts model data as input and outputs updated models, schedules, and metadata, ideal for use cases requiring automated BIM model management and analysis.

Canonical page: https://skillsregistry.net/skills/soewal19-eracore-revit-mcp  
JSON: https://api.skillsregistry.net/v1/skills/soewal19-eracore-revit-mcp

## Description

Connects LLM assistants to Autodesk Revit BIM models, enabling reading metadata, listing elements, creating geometry, batch parameter updates, and exporting schedules. Supports fake mode for testing without Revit and pyRevit mode for live integration.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/crt7iv833h)
- **Repository:** <https://github.com/soewal19/eracore-revit-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "soewal19-eracore-revit-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/soewal19-eracore-revit-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/soewal19-eracore-revit-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt