# RevitMCP

> Use this tool when you need to automate interactions with Autodesk Revit models using natural language commands, enabling AI assistants to query model information, create and modify elements, and perform complex operations. It solves problems of manual model manipulation and provides a standardized interface for AI-powered tools. Ideal for architects, engineers, and designers seeking to streamline Revit model interactions through AI integration.

Canonical page: https://skillsregistry.net/skills/oakplank-revit  
JSON: https://api.skillsregistry.net/v1/skills/oakplank-revit

## Description

A Revit API integration that enables AI assistants to interact directly with Autodesk Revit models through natural language commands. Developed to provide a standardized interface for querying model information, creating and modifying elements, and performing complex operations using the Model Context Protocol. Useful for architects, engineers, and designers seeking to automate and streamline Revit model interactions through AI-powered tools.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** api-integration
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/oakplank-revit)
- **Repository:** <https://github.com/oakplank/revitmcp>

## 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": "oakplank-revit"
    }
  }
}
```

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