Skip to main content
Glama

start_blender

Launch Blender as a managed subprocess for automated 3D tasks, with options to open a blend file, run headless, or execute Python expressions.

Instructions

Launch Blender as a managed subprocess.

Parameters:

  • blend_file: Path to a .blend file to open on startup (optional)

  • blender_exe: Full path to the Blender executable. Auto-detected if omitted (checks BLENDER_EXE env var, PATH, then common install locations).

  • background: True = headless mode (--background), no UI. Useful for rendering.

  • wait_for_addon: Wait up to 30 s for the BlenderMCP addon socket to become reachable on port 9876 (default True). Set False for background jobs that don't use the addon.

  • python_expr: Optional Python expression passed to Blender via --python-expr, e.g. "import bpy; bpy.ops.wm.quit_blender()" for scripted batch runs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
blend_fileNo
blender_exeNo
backgroundNo
wait_for_addonNo
python_exprNo
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description must fully disclose behavioral traits. It mentions background mode, wait_for_addon timeout, and auto-detection of blender_exe, but does not cover what happens on failure, whether it manages Blender lifecycle, or what the return status is. Some gaps remain.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded with the core purpose. Parameter descriptions are bullet-like, easy to scan, and every sentence adds value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 5 parameters and no output schema, the description does not explain the return value or guarantee that Blender is ready. It also omits prerequisites like Blender installation. While it captures key usage details, it is not fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description provides extensive details for all five parameters: blend_file path, blender_exe auto-detection, background mode, wait_for_addon usage (including when to set False), and python_expr examples. This adds significant value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Launch Blender as a managed subprocess.' This provides a specific verb and resource, distinguishing it from sibling tools that perform operations within Blender rather than starting it.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly state when to use this tool versus alternatives. While it is implied that this tool should be used before other Blender operations, there is no guidance on prerequisites (e.g., Blender installed) or when not to use it (e.g., if Blender is already running).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/naab007/blender_mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server