Skip to main content
Glama
MITHRAN-BALACHANDER

Blender MCP Bridge

by MITHRAN-BALACHANDER
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
blender_execA
Execute a Python script inside Blender.

IMPORTANT RULES:
- The script MUST define a main() function and call it
- Use send_status("message") to report progress
- Use bpy.data.* APIs instead of bpy.ops.* when possible
- Script MUST terminate - no infinite loops
- Catch exceptions and handle errors gracefully

Args:
    script: Python code to execute in Blender. Has access to 'bpy' and 'send_status()'.

Returns:
    JSON string with execution results including status and any messages.
get_blender_sceneA
Get information about the current Blender scene.

Returns:
    JSON string with lists of objects, meshes, materials, and collections.
image_to_3d_modelA
Create a 3D model in Blender with colors extracted from an image.

This tool analyzes the provided image to extract dominant colors, then creates
a 3D model in Blender with materials matching those colors.

Args:
    image_data: Base64-encoded image data (can include data URL prefix)
    model_type: Shape type - "cube", "sphere", or "cylinder" (default: "cube")
    model_name: Name for the created 3D object (default: "ImageModel")

Returns:
    JSON string with status, extracted colors, and model information.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A3.7/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct purpose with no overlap: blender_exec runs Python scripts, get_blender_scene retrieves scene information, and image_to_3d_model creates 3D models from images. The descriptions reinforce these distinct functions, making misselection unlikely.

Naming Consistency4/5

The naming follows a consistent verb_noun pattern (blender_exec, get_blender_scene, image_to_3d_model) with clear actions and targets. The minor deviation is that 'blender_exec' uses an abbreviation while others are spelled out, but the pattern remains readable and predictable.

Tool Count3/5

With only 3 tools, the set feels thin for a Blender bridge, as it lacks core operations like modifying objects, rendering, or exporting. While the tools are well-defined, the count is borderline low for the apparent scope of 3D modeling and automation.

Completeness2/5

There are significant gaps in the tool surface for a Blender integration. Missing are essential CRUD operations (e.g., create/update/delete objects), rendering tools, export capabilities, and scene manipulation functions. This will likely cause agent failures when trying to perform common Blender workflows.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources