Blender MCP Fleet prototype

This prototype exposes one MCP dispatcher and fans independent model jobs out to isolated, headless Blender processes. It is intended for multiple agents: each agent submits a job, and each job gets its own directory, .blend, preview, log, and Blender process.

Why this design

The currently installed ahujasid/blender-mcp add-on is a GUI TCP bridge and uses one fixed port by default. A worker pool avoids port routing and avoids cross-contamination between projects. It also makes failures recoverable: a failed worker is just one failed job.

Related MCP server: Blender MCP Server

Run the smoke test

From PowerShell:

Set-Location D:\blender-mcp-fleet\prototype\fleet
python .\smoke_test.py

The test submits four models with two workers, so two Blender jobs run at a time. Results are written under D:\blender-mcp-fleet\prototype\jobs.

Run the MCP dispatcher

The MCP dependency can be installed into a local environment with uv:

Set-Location D:\blender-mcp-fleet\prototype
uv venv --python 3.11 .venv
uv pip install --python .\.venv\Scripts\python.exe "mcp[cli]==1.29.0"

Then register this as a separate MCP entry for testing; it does not replace the current blender entry:

[mcp_servers.blender_fleet]
command = "D:\\blender-mcp-fleet\\prototype\\.venv\\Scripts\\python.exe"
args = ["D:\\blender-mcp-fleet\\prototype\\fleet\\mcp_server.py"]

[mcp_servers.blender_fleet.env]
BLENDER_FLEET_PARALLEL = "2"

The exposed tools are submit_model_job, get_job_status, wait_for_job, list_model_jobs, and fleet_info.

The safe preset kinds include cube, sphere, monkey, tower, robot, spaceship, castle, and solar_system. The last three are useful for a slightly more realistic multi-agent smoke test because they create multiple meshes, materials, lights, and modifiers.

To test the actual MCP stdio handshake without changing Codex configuration:

D:\blender-mcp-fleet\prototype\.venv\Scripts\python.exe .\fleet\mcp_smoke.py

Safety boundaries

The first version only accepts a small allow-listed set of model kinds. It does not execute arbitrary agent-provided Python. A later version can add a reviewed recipe/script mode with per-job timeouts and an explicit workspace allow-list.