
mcp-for-maya
io.github.Xxx91nPublished by GitHub account Xxx91nv0.7.0Updated Oct 30, 2026
AI agents' spatial awareness inside Autodesk Maya: audit, rollback safety, visual loop (Beta)
Overview
MCP server that lets an AI agent inspect, measure, plan, audit and edit Autodesk Maya 3D scenes through Maya's local command port.
- What you can do
- Inspect and measure scenes: full spatial snapshots, per-object inspection, node and scene-graph enumeration, precise clearance and overlap measurements.
- Plan and audit: scene planning, aesthetic analysis, 11-check engineering review with a 0-100 score, custom constraint validation and assertions.
- Edit and execute: run arbitrary Python inside Maya, inject reusable modules, create cameras and orbit animations.
- Recover and export: in-memory checkpoints and rollback, export whole scenes or selections to FBX, OBJ or USD.
- Capture and assets: viewport screenshots and playblast previews in GUI sessions, plus Poly Haven model search and import with automatic texture wiring.
- Manage sessions…
- When to use it
- Use it when you want an AI assistant to work inside a live Maya session for 3D modeling, layout, lighting and camera work, or to audit an existing scene against spatial and production rules. It suits artists and technical directors who want inspect-then-verify editing rather than blind script generation.
- Requirements
- Local Python 3.10 or newer on the host, installed from PyPI or run with uvx; Maya 2023 or newer with a Python commandPort open (typically localhost:7001), optionally persisted via userSetup.py. Optional environment variables MAYA_MCP_INCLUDE_PORTS, MAYA_MCP_EXCLUDE_PORTS, MAYA_MCP_DISABLE_EXECUTE, MAYA_MCP_DISABLE_WRITE_MODULE, MAYA_MCP_DISABLE_ARBITRARY and MAYA_MCP_SAFE_MODE tune scanning and policy. Asset tools need outbound HTTPS to Poly Haven.
Installation
In SourceWeft
- Open mcp-for-maya in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
English | 简体中文
[mcp-for-maya — Give AI agents eyes inside Autodesk Maya]
mcp-for-maya
MCP server giving AI agents spatial awareness of Autodesk Maya scenes
[CI] [PyPI] [License: MIT] [Python]
What this is
mcp-for-maya is a Model Context Protocol (MCP) server that lets AI agents (such as Codex and Claude) directly control Autodesk Maya for 3D modeling, scene planning, and production-ready work.
Core capability: AI no longer writes code blindly. It inspects scene objects, materials, and spatial relationships at any time, auditing changes against real engineering rules.
[Quick Start][!WARNING] This server runs Python code directly inside Maya by design, not by accident. For details, see docs/threat-model.md.
For live captures and examples, see docs/assets/showcase.md.
1. Install
2. Connect Maya
Option A: Automatic setup (recommended)
Once the MCP server is running, the agent automatically calls maya_setup_guide to guide you through connecting:
- Make sure Maya is open
- Give the agent any instruction (like "check my Maya scene")
- If not connected, the agent runs diagnostics and can install
userSetup.py(merges safely with backup before writing) - Restart Maya, and the command port opens automatically
Option B: Manual setup
Run this in Maya's Script Editor:
Tip: Open Script Editor via Maya menu → Windows → General Editors → Script Editor. Make sure the tab language is set to Python (not MEL).
Option C: Persistent auto-connect
Save the following code as userSetup.py in your Maya scripts folder:
Multiple Maya instances
Each commandPort binds to a specific host:port. A second instance cannot use the same port, so each Maya instance must use its own port. Typical layout:
Run cmds.commandPort(name=":<port>", sourceType="python") in each instance's Script Editor (or each one's userSetup.py). Auto-scan is the primary method — the server regularly scans local Maya listening ports and sets up connections. If an instance is missed, call add_session(host, port) manually. If port scanning touches other local TCP services, set MAYA_MCP_INCLUDE_PORTS=7001,7002 (comma-separated, ranges like 7005-7010 supported) to limit the scan, or use MAYA_MCP_EXCLUDE_PORTS=<port> to ignore specific ports.
Note: A commandPort does not persist across sessions — it closes when Maya quits. To keep it persistent, add it to userSetup.py (Option C).
Troubleshooting
3. Configure your MCP client
Codex ~/.codex/config.toml:
For git source installs: args = ["--from", "git+https://github.com/Xxx91n/mcp-for-maya.git", "mcp-for-maya"]. For local source builds, set command = "python", args = ["-m", "maya_mcp_server"], and point PYTHONPATH to <repo>/src in env.
4. Start using it
Chat naturally in your agent:
"Check out what's in my Maya scene, then put together a display shelf by the entrance"
The AI automatically calls scene_snapshot() → inspects the scene → builds the model → audits the result with scene_review().
Every scene edit follows the ICEV workflow (also provided as an agent skill card in skills/icev-workflow):
- INSPECT: Call
scene_snapshot()to capture full spatial scene data - COMPUTE: Calculate positions, sizes, and spacing from the spatial data
- EXECUTE: Run Maya Python code via
execute_code() - VERIFY: Check the outcome with
scene_assert()+scene_review(); GUI sessions can use visual tools to verify visually
25 MCP tools in total.
Tools in detail
Spatial awareness
Engineering audit
Camera planning
Disaster recovery
Assets (Poly Haven, host-side download)
Scene export
Visual loop (GUI sessions only)
CoS notation
Default output uses Chain-of-Symbol notation to compress scene data. The original research paper reports roughly 65% token savings compared to JSON on demo scenes (arXiv:2305.10276, -65.8%).
Agent skills
The repository includes two Experimental skill cards (under the skills/ folder):
scene_review() provides 11 universal checks (scores 0-100, normalized by rule weight):
Security & privacy
- Zero telemetry: No tracking, no phone-home. This project contains zero tracking or unsolicited outgoing network code, as you can verify in source. The only outgoing network calls are from the two asset tools: they access
api.polyhaven.com/dl.polyhaven.org|.comover HTTPS only when invoked (with domain allowlist, MD5 check, and file size limits inpolyhaven.py). - Local single-user: The command port binds to localhost only. Connected MCP clients are treated as trusted callers.
- Safety net: A unified pipeline (
pipeline.py+security.py) checks parameters, enforces token-bucket rate limits (~100 calls/60s for reads, ~20 calls/60s for writes per session), scans patterns (warn-only by default), and maintains an independent JSONL audit log across all 25 tools. It catches accidental mistakes rather than malicious clients. See docs/threat-model.md for the complete threat model. - Transactional safety:
scene_checkpointandscene_rollbackoffer in-memory snapshots and explicit rollback (snapshots do not keep undo history; file references are flattened). - Strict policy mode (optional): Set
MAYA_MCP_DISABLE_EXECUTE=1,MAYA_MCP_DISABLE_WRITE_MODULE=1, orMAYA_MCP_DISABLE_ARBITRARY=1(disables all three) to remove code execution tools fromtools/listand reject calls with[policy_disabled]. Read-only tools remain active. These are guardrails against misuse, not impenetrable security boundaries against a malicious agent—agents holdingexecute_codeare already inside the trust boundary. They simply reduce the blast radius during demos, testing, or in CI sandboxes. See docs/threat-model.md and error codes in docs/guide/error-codes.md. safe_modeAST gate (optional): WhenMAYA_MCP_SAFE_MODE=1is set (off by default), code payload tools remain listed, but theircodeparameters must pass an AST allowlist that denies everything else by default: imports are limited to standard packages (maya,math,json,re,collections,itertools,functools,dataclasses,typing), blocked builtin functions reject upon reference rather than just call (eval,exec,open,__import__, getattr, setattr, etc.), accessing__builtins__or dunder attributes is rejected, and unparseable input is rejected immediately. Blocked calls fail with[safe_mode_rejected], reporting the violated rule ID and logging to the audit trail. Successful calls return amode: "safe"field, and the tool description adds aBoundary:notice. DISABLE flags take priority by removing tools first—safe_mode only restricts what stays. Like DISABLE flags, this serves as a safety net against accidents, not an impenetrable barrier. See docs/threat-model.md and error codes in docs/guide/error-codes.md.- Vulnerability reporting: See SECURITY.md.
Requirements
Development
For contribution workflow, see CONTRIBUTING.md; for changelog, see CHANGELOG.md.
Credits
Forked from chadrik/maya-mcp-server, retaining its MIT license.
Source: README.md at commit 81a17b5
Tools
0Version history
3- v0.7.0LatestOct 29, 2026
- v0.6.0Oct 26, 2026
- v0.5.0Sep 30, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts