# revit-mcp-hardened

> revit-mcp-hardened — elkhouryrafik-boop-revit-mcp-hardened. Use this tool when you need to inspect and manipulate Autodesk Revit models programmatically, enabling large language models (LLMs) to interface with Revit via pyRevit. It solves problems related to automated model analysis and modification, providing a secure interface with token authentication and capability profiles. This tool is ideal for use cases requiring automated Revit model processing, such as design optimization or data extraction, with inputs including model files and API requests, and outputs including modified models and analysis results.

Canonical page: https://skillsregistry.net/skills/elkhouryrafik-boop-revit-mcp-hardened  
JSON: https://api.skillsregistry.net/v1/skills/elkhouryrafik-boop-revit-mcp-hardened

## Description

Hardened MCP server for Autodesk Revit enabling LLMs to inspect and manipulate Revit models via pyRevit, with token authentication and capability profiles.

## Trust

- **Trust score (0–1):** 0.33
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/oijfpl0ord)
- **Repository:** <https://github.com/elkhouryrafik-boop/revit-mcp-hardened>

## 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": "elkhouryrafik-boop-revit-mcp-hardened"
    }
  }
}
```

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