Skip to main content
Glama

blender_shapekeys

Manage facial shape keys for lip sync, blinks, expressions, and VRM avatars, automating viseme generation and weight control.

Instructions

Comprehensive shape key management for facial animation and VRM avatars.

Handles viseme creation for lip sync, blink animations, facial expressions, and VRM compliance checking for VR platforms.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
frameNoAnimation frame to set weights at
operationNoShape key operation typecreate_viseme_shapekeys
target_meshNoTarget mesh object (defaults to active)
viseme_typeNoType of viseme system ("vrm", "standard", "custom")vrm
base_visemesNoBase viseme weights for expression
blink_weightNoBlink component weight for expression
auto_generateNoWhether to auto-generate basic viseme shapes
viseme_weightsNoDictionary of viseme names to weights (0.0-1.0)
base_expressionNoBase expression shape key to start from
blink_intensityNoHow closed the eyes should be (0.0-1.0)
expression_nameNoName for the facial expressionexpression
eyelid_verticesNoSpecific vertex indices for eyelid control
include_statisticsNoInclude deformation statistics in analysis
additional_modifiersNoAdditional shape key modifiers

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

Annotations include readOnlyHint=false, destructiveHint=false, and idempotentHint=false, but the description adds no behavioral details such as side effects on mesh shape keys, reversibility, or prerequisites like existing meshes. It only lists use cases without disclosing mutation behavior or error conditions beyond what annotations imply.

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

Conciseness4/5

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

Two sentences, front-loaded with the general purpose and then listing specific capabilities. It is concise and readable, though the word 'Comprehensive' is somewhat generic and the description could be tightened further.

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

Completeness2/5

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

Given the tool's complexity—14 parameters, an operation enum, and a rich schema—the description is too high-level. It does not explain how operations map to parameters, default behaviors, or what 'VRM compliance checking' entails, leaving the agent to infer critical selection and invocation details from the schema alone.

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

Parameters3/5

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

Schema description coverage is 100%, with all 14 parameters documented including the operation enum and per-parameter descriptions. The tool description itself adds no parameter-specific meaning, so the baseline score of 3 applies.

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?

Description clearly identifies the tool's purpose as 'shape key management for facial animation and VRM avatars' and enumerates specific capabilities: viseme creation for lip sync, blink animations, facial expressions, and VRM compliance checking. This distinguishes it from sibling tools like blender_animation, blender_rigging, and blender_vrm_metadata.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives such as blender_animation or blender_vrm_metadata. The description implies usage for facial/VRM shape key work, but does not state exclusions, prerequisites, or alternative scenarios.

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

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/sandraschi/blender-mcp'

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