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Coming from That project was archived on Feb 26, 2026. RevitMCPBridge2026 is the actively maintained alternative with 705+ endpoints, named pipe communication (no crashes), and a 113-file architectural knowledge base. See Quick Start to get running in minutes.


What is this?

RevitMCPBridge is a Revit add-in that exposes the entire Revit API through the Model Context Protocol (MCP) via named pipes. AI systems — Claude, GPT, custom agents — can read, create, modify, and validate anything in a Revit model programmatically. No Dynamo. No manual steps. Just send JSON, get results.

For AEC professionals: Your AI assistant can now open your Revit model and actually do things — create walls, place doors, generate sheets, check code compliance, produce construction documents.

For developers: 705+ typed endpoints with parameter validation, transaction management, and structured error responses. Connect any language that can write to a named pipe.

Why Named Pipes Instead of HTTP?

Revit is single-threaded. Every API call must execute on the main UI thread.

Approach

What Happens Under Load

HTTP server

Competes for the main thread. Multiple concurrent AI requests cause timeouts, dropped connections, and crashes.

Named pipes

Uses Revit's own ExternalEvent queue. Requests are serialized through the same mechanism Revit uses internally. Zero thread contention, zero crashes.

Every other Revit MCP implementation uses HTTP. They work for simple demos but break under real workloads. Named pipes are why this bridge can handle 705+ endpoints reliably.

Before and After

Before RevitMCPBridge:

You: "Create a sheet set for these 12 floor plans"
AI:  "Here are the steps you should follow manually in Revit:
      1. Go to View > Sheet Composition > New Sheet
      2. Select your title block...
      3. Repeat 12 times..."

After RevitMCPBridge:

# AI executes directly in Revit
for i, view_id in enumerate(floor_plan_ids):
    call_revit("createSheet", {
        "sheetNumber": f"A1.{i+1}",
        "sheetName": f"Floor Plan - Level {i+1}",
        "titleBlockName": "E1 30x42 Horizontal"
    })
    call_revit("placeViewOnSheet", {
        "sheetId": sheet_id,
        "viewId": view_id,
        "locationX": 1.5,
        "locationY": 1.0
    })
# 12 sheets created, views placed, titled — in seconds

What It Enables

Capability

Methods

Example

Read any model data

Parameters, elements, geometry, schedules

Extract every door schedule to JSON

Create elements

Walls, doors, windows, rooms, structural, MEP

Build a floor plan from a PDF specification

Modify elements

Move, resize, reparameter, retype

Batch-update 200 door fire ratings

Generate documents

Sheets, views, schedules, annotations

Produce a full CD set automatically

Validate models

Code compliance, clash detection, QC

Check egress paths against IBC requirements

AI autonomy

Goal execution, learning, self-healing

"Set up this project" → 360 sheets, done

Scale

  • 705+ MCP endpoints across 25+ categories

  • 146 C# source files, 13,000+ lines

  • 113 knowledge files of architectural domain expertise (building codes, room standards, MEP systems, material specs)

  • 68 unit tests with NUnit

  • 5 levels of autonomy — from direct API calls to autonomous goal execution

API Categories

Category

Endpoints

What It Does

Walls

11

Create, modify, split, join, query wall elements

Doors & Windows

13

Place openings, configure hardware, set fire ratings

Rooms

10

Create rooms, compute areas, tag, set finishes

Views

12

Create plans, sections, elevations, 3D views

Sheets

11

Create sheets, place viewports, manage title blocks

Schedules

34

Create/modify schedules, export data, configure fields

Families

29

Load families, place instances, query types

Parameters

29

Get/set any parameter on any element

Structural

26

Beams, columns, foundations, framing

MEP

35

Ducts, pipes, equipment, electrical

Details

33

Detail lines, filled regions, detail components

Filters

27

View filters, graphic overrides, visibility

Materials

27

Material creation, assignment, appearance

Phases

24

Construction phases, phase filters

Worksets

27

Workset management for workshared models

Annotations

33

Dimensions, tags, text notes, keynotes

Intelligence

35

AI autonomy, learning, goal execution, self-healing

Sheet Patterns

11

Intelligent sheet numbering and organization

Viewport Capture

7

View capture, camera control

Rendering

7

AI-assisted rendering via Stable Diffusion

System

6

Health check, version, stats, method listing

Quick Start

Prerequisites

  • Autodesk Revit 2025 or 2026

  • .NET Framework 4.8

  • Visual Studio 2022 (for building from source)

Install

# Option 1: Installer script
git clone https://github.com/WeberG619/RevitMCPBridge2026.git
cd RevitMCPBridge2026
.\scripts\deploy\Install-RevitMCPBridge.ps1

# Option 2: Manual
msbuild RevitMCPBridge2026.csproj /p:Configuration=Release
copy bin\Release\RevitMCPBridge2026.dll "%APPDATA%\Autodesk\Revit\Addins\2026\"
copy RevitMCPBridge2026.addin "%APPDATA%\Autodesk\Revit\Addins\2026\"
copy appsettings.json "%APPDATA%\Autodesk\Revit\Addins\2026\"

Connect

Start Revit, then from any language:

import struct, json

PIPE_NAME = r'\\.\pipe\RevitMCPBridge2026'

def call_revit(method, params=None):
    """Call any Revit method via named pipe."""
    import win32file, win32pipe
    handle = win32file.CreateFile(
        PIPE_NAME, win32file.GENERIC_READ | win32file.GENERIC_WRITE,
        0, None, win32file.OPEN_EXISTING, 0, None
    )
    request = json.dumps({"method": method, "params": params or {}}).encode()
    win32file.WriteFile(handle, struct.pack('<I', len(request)) + request)
    size = struct.unpack('<I', win32file.ReadFile(handle, 4)[1])[0]
    data = win32file.ReadFile(handle, size)[1]
    handle.Close()
    return json.loads(data)

# Verify connection
print(call_revit("healthCheck"))
# {"status": "healthy", "documentOpen": true, "methodCount": 705}

# List all available methods
print(call_revit("getMethods"))
# {"methods": ["getVersion", "createWall", ...], "count": 705}

Note: The bridge communicates via Windows named pipes (\\.\pipe\RevitMCPBridge2026), not HTTP. This provides direct in-process communication with Revit. For a simpler Python wrapper, see the python/ directory.

Your first wall

# Create a wall
result = call_revit("createWall", {
    "startX": 0, "startY": 0,
    "endX": 20, "endY": 0,
    "wallTypeName": "Generic - 8\"",
    "levelName": "Level 1",
    "height": 10
})
print(result)
# {"success": true, "elementId": 123456, "length": 20.0}

Autonomy Levels

The bridge supports 5 levels of AI autonomy:

Level

Name

What It Does

1

Basic Bridge

Direct API translation. Send method, get result.

2

Context Awareness

Tracks element relationships, maintains session context.

3

Learning & Memory

Stores corrections, learns patterns for future use.

4

Proactive Intelligence

Detects workflow gaps, suggests next steps, anticipates needs.

5

Full Autonomy

Executes high-level goals with self-healing and guardrails.

Level 5 Example

# "Set up construction document sheets" — one command
call_revit("executeGoal", {
    "goalType": "create_sheet_set",
    "parameters": {
        "viewIds": [123456, 234567, 345678],
        "sheetPattern": "A-{level}.{sequence}"
    }
})
# Creates sheets, places views, adds title blocks, numbers everything

# Safety guardrails
call_revit("configureAutonomy", {
    "maxElementsPerTask": 100,
    "allowedMethods": ["createWall", "placeDoor", "createSheet"],
    "blockedMethods": ["deleteElements"],
    "requireApprovalFor": ["deleteSheet"]
})

Knowledge Base

The bridge includes 113 files of architectural domain knowledge:

Category

Files

Coverage

Building Types

17

Residential, commercial, healthcare, education, hospitality, industrial

Building Codes

15

IBC, Florida Building Code (complete), NYC, California, Chicago

Structural & Envelope

12

Foundations, framing, walls, roofs, glazing, mass timber

MEP Systems

10

HVAC, electrical, plumbing, fire protection, elevators

Interior & Finishes

9

Kitchen/bath, materials, millwork, acoustics, door hardware

Codes & Regulatory

9

Accessibility, egress, energy, zoning, permitting

Project Delivery

10

Cost estimating, specifications, construction admin

Documentation

7

CD standards, annotation standards, detail libraries

This knowledge base enables AI agents to make code-compliant, architecturally correct decisions without requiring the user to specify every standard.

Connection to the Autonomy Engine

RevitMCPBridge is the flagship integration for the Autonomy Engine. When connected:

  • Goal tracking — "Set up this project" becomes a tracked goal with sub-goals and progress

  • Correction learning — BIM-specific mistakes get stored and injected into future Revit tasks

  • Alignment injection — Every Revit agent gets compiled corrections for the BIM domain

  • Coordination — Multiple agents can work on the same model with resource locking

User Goal: "Create construction documents"
    ↓
Autonomy Engine decomposes into plan:
    1. Create sheet set (SheetMethods)
    2. Place views on sheets (ViewMethods)
    3. Add annotations (AnnotationMethods)
    4. Generate schedules (ScheduleMethods)
    5. QC check (Intelligence)
    ↓
Each step gets BIM-domain alignment injection
    ↓
Corrections from past sessions prevent known mistakes
    ↓
Progress cascades to parent goal: 100%

Configuration

{
  "Pipe": {
    "Name": "RevitMCPBridge2026",
    "TimeoutMs": 30000,
    "MaxConnections": 5
  },
  "Logging": {
    "Level": "Information",
    "LogDirectory": "%APPDATA%/RevitMCPBridge/logs"
  },
  "Autonomy": {
    "Enabled": true,
    "MaxRetries": 3,
    "MaxElementsPerBatch": 100
  }
}

Architecture

graph LR
    subgraph "AI Side"
        CL[Claude / GPT / Custom Agent]
        AE[Autonomy Engine]
        CL --> AE
    end

    subgraph "Bridge"
        NP[Named Pipe Server]
        MR[Method Router]
        TV[Transaction Validator]
        NP --> MR --> TV
    end

    subgraph "Revit Side"
        RA[Revit API]
        DOC[Active Document]
        TV --> RA --> DOC
    end

    AE --> |JSON over pipe| NP
    DOC --> |result| NP --> |JSON response| AE

    style CL fill:#4A90D9,color:#fff
    style AE fill:#E74C3C,color:#fff
    style NP fill:#2ECC71,color:#fff
    style RA fill:#F39C12,color:#fff

Development

# Build
msbuild RevitMCPBridge2026.csproj /p:Configuration=Release

# Run tests
dotnet test tests/RevitMCPBridge.Tests.csproj

# Smoke test (requires Revit running)
python tests/smoke_test.py

Troubleshooting

Problem

Solution

Connection refused

Ensure Revit is running and add-in loaded (check ribbon)

Method not found

Run getMethods to list available methods. Names are case-sensitive.

Operation failed

Check that a document is open. Verify element IDs exist.

Timeout

Close any blocking Revit dialogs. Click in the drawing area.

Comparison with Other Revit MCP Implementations

Feature

RevitMCPBridge2026

revit-mcp (archived)

revit-mcp-commandset (archived)

Status

Active

Archived Feb 2026

Archived Feb 2025

Endpoints

705+

~30

~50

Transport

Named pipes

HTTP

HTTP

Revit versions

2025, 2026

2025

2025

Knowledge base

113 files

None

None

Autonomy levels

5 (basic → full)

1

1

Transaction safety

Built-in

Manual

Manual

License

MIT License. See LICENSE.

Author

Weber GouinBIM Ops Studio

The first open-source bridge connecting AI to Autodesk Revit through the Model Context Protocol.

Contributing

See CONTRIBUTING.md for guidelines. Issues and PRs welcome.


-
security - not tested
A
license - permissive license
-
quality - not tested

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