ellmos Blender Use MCP
This server provides MCP tools for headless, stateless Blender automation and asset-QA verification.
Locate the Blender executable automatically via explicit path, BLENDER_EXE, standard install locations, or PATH.
Run arbitrary Blender Python scripts in background mode with optional arguments, timeout guarding, and bounded output tails.
Verify FBX reimports in headless Blender: imports the FBX and returns deterministic JSON with mesh count, empty count, material count, material slot assignments, and missing required prefixes.
Render four-view visual verification of FBX assets to detect problems structural checks miss, such as unapplied rotation, floating parts, pivot offsets, transform residuals, and stray empties.
Use the verification results as a CI/CD asset-QA gate, with no add-on, no TCP daemon, no persistent process, zero network egress, and ephemeral temp-file cleanup.
Provides headless Blender asset QA and FBX reimport verification, enabling automated checks for mesh count, material count, and naming prefixes in CI pipelines.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@ellmos Blender Use MCPverify FBX reimport for /models/prop.fbx"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
ellmos Blender Use MCP
🇩🇪 Deutsche Version
Part of the ellmos-ai family and the open-bricks open-source initiative.
Quick Navigation
Language / Sprache: 🇬🇧 English | 🇩🇪 Deutsch
1. Key Capabilities • 2. Target Personas & Discoverability • 3. Comparative Matrix • 4. Architecture & Topology • 5. Verification Lifecycle • 6. Tool Suite • 7. FBX Verification Deep Dive • 8. Visual Verification Deep Dive • 9. General Primitives • 10. CI/CD Integration • 11. Governance Invariants • 12. Security Policy • 13. Installation • 14. Configuration • 15. Level 1 SBOM • 16. Ecosystem • 17. LLM Context • 18. License & Statutory Notice
1. Key Capabilities
An asset-QA tool for game and 3D asset pipelines: verify that an exported FBX actually reimports cleanly in headless Blender — mesh count, material count, and required naming prefixes checked automatically, with a deterministic JSON result instead of a manual eyeball pass. blender_verify_fbx_reimport is the core structural tool and blender_verify_visual its visual counterpart — the first counts meshes and checks name prefixes, the second renders four views and measures geometry that counting cannot see. blender_locate and blender_run_script are the general-purpose primitives both are built on.
No add-on. No TCP port. No background daemon. This server does not install anything into Blender, does not open a socket for a running Blender instance to connect to, and does not keep Blender resident. Each call spawns blender --background --python <script.py>, waits for a bounded, timeout-guarded exit, and returns the result — headless and stateless by design. It does not download assets and does not collect telemetry.
How this differs from other Blender MCP servers. Most Blender MCP projects (e.g. ahujasid/blender-mcp, the official Blender Labs MCP server) drive a live, running Blender GUI over a TCP/add-on bridge for interactive scene editing — a different use case with a different trust model (an open socket, an installed add-on, a persistent process). This server instead targets CI-style, one-shot asset verification: run it in a pipeline step, get a pass/fail JSON, move on. If you need live GUI control, use a reviewed Blender MCP add-on separately (see Safety below).
AI / LLM Integration & Machine-Readable Context: AI assistants (Claude, Codex, Gemini) can read llms.txt for machine-readable context, search phrases, and tool documentation. Regression test suites guard privacy hygiene and runtime memory safety.
CI & Asset Pipeline Automation: Use blender_verify_fbx_reimport as an automated gate before committing 3D assets to source control. It flags missing prefixes (e.g., SM_, M_), unexpected mesh counts, or broken material assignments without human intervention.
Related MCP server: blender-MCP
2. Target Personas & High-Intent Discoverability
[PERSONA-01] Indie & AAA Game Technical Artists & 3D Pipeline TDs
Profile: Technical Artists managing FBX/GLTF asset pipelines for Unreal Engine, Unity, Godot, and custom C++ game engines.
Pain Point: Exported 3D assets frequently have unapplied rotation (lying on their side in-engine), broken pivot offsets, missing
SM_/M_prefixes, or unassigned materials that slip past manual review.High-Intent Queries:
blender fbx reimport verification mcp,blender headless asset qa gate,automated fbx naming convention check,detect unapplied rotation fbx blender.How We Solve It: One-shot structural reimport verification and 4-view visual geometry checks without having to open the Blender GUI.
[PERSONA-02] CI/CD Automation & Build Infrastructure Engineers
Profile: DevOps and Build Engineers responsible for automated asset validation gates in GitHub Actions, GitLab CI, or Jenkins.
Pain Point: Traditional Blender automation tools require installing graphical add-ons or running interactive background sockets, which fail in headless containerized runners.
High-Intent Queries:
headless blender asset qa mcp server,github actions blender fbx qa gate,blender background script ci cd verification,blender mcp no add-on no tcp port.How We Solve It: Stateless
blender --backgroundexecution with strict 15-minute runaway timeouts, bounded 8 KB memory tails, zero add-ons, and deterministic JSON exit codes.
[PERSONA-03] Autonomous AI Agent Engineers (Claude, Codex, Gemini)
Profile: Developers deploying autonomous AI coding agents for procedural 3D generation, asset processing, and game prototyping.
Pain Point: AI agents need to inspect and verify 3D assets without socket leaks, zombie processes, or uncontrolled memory consumption.
High-Intent Queries:
mcp server fbx mesh material verification,ai agent blender 3d asset inspection,blender four-view rendering mcp,llm tool headless blender.How We Solve It: Native Model Context Protocol (MCP) server with comprehensive llms.txt documentation, robust
taskkill /T /Fprocess tree termination, and fail-closed temporary file cleanup.
[PERSONA-04] Enterprise Game Studio Compliance & Security Officers
Profile: Security Officers and Compliance Managers safeguarding proprietary game IP and development workstations.
Pain Point: Third-party DCC tools frequently open local network ports, dial remote telemetry servers, or require administrator privileges.
High-Intent Queries:
offline blender mcp zero egress,air gapped 3d asset verification,unprivileged blender asset qa,zero copyleft mcp tool.How We Solve It: Strict
RunAsInvokernon-elevation certification, 100% offline zero-egress guarantee, zero runtime telemetry, and Level 1 SBOM with 0% copyleft licenses.
3. 10-Dimension Comparative Matrix vs. Alternatives
Invariant / Dimension | [1] | [2] Interactive Blender MCP (TCP Add-on) | [3] Ad-Hoc Python Scripts | [4] Heavy DCC Suites (Maya / 3ds Max QA) | [5] Cloud SaaS 3D Checkers (Sketchfab) |
INV-LOCAL-01: Network & Air-Gap | 100% Offline / Zero-Egress (0 network calls) | Open TCP localhost listener required | Local, but unbounded network access | Local, but heavy license server polling | Remote SaaS upload required (Egress risk) |
INV-HEADLESS-02: Add-on Burden | Zero Add-ons (works out of the box) | Requires Blender add-on installation | No add-on required | Proprietary plugin installations | Web browser or heavy client upload |
INV-SEC-03: Privilege Model | Unprivileged RunAsInvoker (User mode) | User mode, but open socket attack surface | Unrestricted script execution | Administrator/Service installation | SaaS cloud security boundary |
INV-BOUND-04: Memory Bounding | Hard Tail Buffer (8 KB - 50 KB max) | Unbounded GUI session memory | Unbounded console output memory | Unbounded workstation memory footprint | Cloud processing quotas |
INV-INTEG-05: Structured JSON QA | Deterministic Machine-Readable JSON | Text prompt / chat responses | Unstructured stdout prints | XML / propriety log reports | Web dashboard visualization |
INV-VISUAL-06: 4-View Geometry | Standardized 4-View Render Pipeline | Manual GUI eyeball rotation | Requires custom camera scripts | Manual viewport navigation | Single WebGL model viewer |
INV-CLEAN-07: Ephemeral Cleanup | Fail-Closed Automated Temp Purge | Persistent scene state in memory | Leftover .py/.blend scratch files | Heavy project temp directories | Remote cloud storage retention |
INV-CROSS-08: Cross-Platform | Windows, Linux, macOS Parity | Dependent on GUI desktop support | OS-dependent path handling | OS-constrained (primarily Windows) | Platform-independent browser |
INV-SYNC-09: Lock & Sync Defense | Multi-Host Lock & Sync Hardened | Vulnerable to file locking collisions | No lock awareness | Heavy proprietary file locks | No multi-device git discipline |
INV-SLA-10: Security SLA | 48h Intake / 5d Triage Commitment | Community best-effort (no SLA) | No formal support | Enterprise support contract required | Generic SaaS ticket queue |
4. Architecture & Component Topology
graph TD
subgraph Client ["AI Assistant & Client Environment"]
AI["AI Agent (Claude / Codex / Gemini)"]
Config["MCP Configuration (npx / node)"]
end
subgraph Server ["ellmos Blender Use MCP Server"]
MCP["MCP Protocol Server (src/index.js)"]
subgraph Tools ["Tool Handlers"]
T1["blender_verify_fbx_reimport"]
T2["blender_run_script"]
T3["blender_locate"]
T4["blender_verify_visual"]
end
Safety["Timeout & Tail Buffer Guard (8k chars)"]
end
subgraph Subprocess ["Headless Subprocess (Isolated)"]
Exe["Blender Executable (blender --background)"]
Python["Temp Python Verification Script"]
FBX["Target FBX Asset File"]
JSONOut["Deterministic JSON Result"]
end
AI -->|JSON-RPC Request| MCP
MCP --> Tools
T1 -->|Generates script & spawns| Exe
T2 -->|Executes arbitrary python| Exe
T3 -->|Locates binary| Exe
T4 -->|Generates visual verification script & spawns| Exe
Exe --> Python
Python --> FBX
FBX -->|Mesh / Material / Naming QA| JSONOut
JSONOut --> Safety
Safety -->|Bounded Response| AI
style Client fill:#1e1e2e,stroke:#89b4fa,stroke-width:1px
style Server fill:#181825,stroke:#cba6f7,stroke-width:1px
style Subprocess fill:#11111b,stroke:#a6e3a1,stroke-width:1px
5. Headless Asset-QA Verification Lifecycle
sequenceDiagram
autonumber
actor Client as AI Assistant / CI Pipeline
participant Server as ellmos Blender Use MCP
participant Resolver as Blender Resolver
participant Process as Headless Subprocess
participant Python as Blender Python Engine
participant FS as Local Filesystem (FBX)
Client->>Server: Call blender_verify_fbx_reimport(fbxPath, requiredPrefixes)
Server->>Resolver: Resolve Blender Executable (blender_locate / BLENDER_EXE / Registry / PATH)
Resolver-->>Server: Return Validated Executable Path
Server->>FS: Write Temp Python Verification Script
Server->>Process: Spawn blender --background --python script (timeout-guarded)
Process->>Python: Execute Verification Script
Python->>FS: bpy.ops.import_scene.fbx(filepath=fbxPath)
FS-->>Python: Parse Mesh Objects & Material Slots
Python->>Python: Validate Naming Prefixes, Object Counts & Hierarchy
Python->>FS: Write Output JSON Verification Result
Process-->>Server: Process Exit (Exit Code 0 / Bounded Tail Buffer)
Server->>FS: Read Result & Clean Up Temp Verification Script
Server-->>Client: Deterministic JSON Result (meshCount, materialCount, missingPrefixes, ok)
6. Tool Suite & Verification Matrix
Tool | Purpose | Primary Output | Memory Guard |
| Generate a temporary Blender verification script, import an FBX, and write a JSON result with mesh/material counts and missing required prefixes. | JSON Report | Bounded 8 KB Tail |
| Render four views of an FBX and check geometry a structural reimport cannot see: unapplied rotation, floating parts, pivot outside the model, transform residuals, stray empties. | 4 PNGs + JSON | Bounded 8 KB Tail |
| Run | Script Tail Text | 8 KB - 50 KB Max |
| Resolve the Blender executable from an explicit path, | Resolved Path | Zero Subprocess |
7. blender_verify_fbx_reimport Deep Dive & Schema
Imports an FBX file into headless Blender and verifies mesh count, empty count, material count, material slot assignments, and required naming prefixes.
Parameters
Parameter | Type | Required | Default | Description |
|
| Yes | — | Target FBX asset file path to verify. |
|
| No |
| Path where structured JSON verification results will be written. |
|
| No |
| List of naming prefixes required on meshes or empties (e.g. |
|
| No | auto-detect | Custom path to the Blender executable ( |
|
| No |
| Process execution timeout in milliseconds (max: |
Example Invocation
{
"fbxPath": "assets/models/SM_Watchtower_01.fbx",
"requiredPrefixes": ["SM_", "M_"]
}Deterministic Output Schema
{
"ok": true,
"blender": "C:\\Program Files\\Blender Foundation\\Blender 4.2\\blender.exe",
"fbxPath": "C:\\projects\\game\\assets\\models\\SM_Watchtower_01.fbx",
"resultPath": "C:\\projects\\game\\assets\\models\\verify_reimport_result.json",
"exitCode": 0,
"timedOut": false,
"durationMs": 1820,
"outputTruncated": false,
"verification": {
"ok": true,
"fbx": "C:\\projects\\game\\assets\\models\\SM_Watchtower_01.fbx",
"mesh_count": 3,
"empty_count": 0,
"material_count": 2,
"materials": [
"M_Stone_Brick",
"M_Wood_Trim"
],
"missing_prefixes": [],
"script_free": true
}
}
8. Visual Verification Deep Dive & 4-View Geometry
Renders four views of an FBX and checks geometry that a structural reimport cannot see.
blender_verify_fbx_reimport counts meshes and checks name prefixes — it cannot tell you that a mesh is lying on its side, that a part floats away from the assembly, or that the pivot sits outside the model. This tool does, and it produces the renders to look at.
{ "fbxPath": "kit.fbx", "outDir": "verify_visual", "expectHeight": "2.5,3.5" }Four-View Orthogonal Projection & Failure Detection
+---------------------------------------+---------------------------------------+
| TOP VIEW | PERSPECTIVE VIEW |
| (XY Plane) | (Isometric) |
| | |
| Detects: X/Y planar alignment, | Detects: Overall silhouette, |
| bounding box symmetry, footprint | complex assembly integration |
+---------------------------------------+---------------------------------------+
| FRONT VIEW | SIDE VIEW |
| (XZ Plane) | (YZ Plane) |
| | |
| Detects: Model height, Z-grounding, | Detects: Depth errors, floating vs |
| upright orientation (lying down) | resting parts, pivot offset |
+---------------------------------------+---------------------------------------+Detected failure classes: unapplied rotation, floating parts in multi-part assets, pivot/origin outside the bounding box, transform residuals in the export, stray empties.
Deterministic Output Schema
{
"ok": true,
"blender": "C:\\Program Files\\Blender Foundation\\Blender 4.2\\blender.exe",
"fbxPath": "C:\\projects\\game\\kit.fbx",
"outDir": "C:\\projects\\game\\verify_visual",
"exitCode": 0,
"timedOut": false,
"durationMs": 3450,
"outputTruncated": false,
"verification": {
"ok": true,
"fails": [],
"warns": [],
"metrics": {
"dimensions": [2.45, 1.82, 4.10],
"center": [0.0, 0.0, 2.05],
"pivotAtOrigin": true,
"unappliedRotation": false
}
},
"renders": {
"view_front": "verify_visual/view_front.png",
"view_side": "verify_visual/view_side.png",
"view_top": "verify_visual/view_top.png",
"view_perspective": "verify_visual/view_perspective.png"
}
}Why four views and not one: a single front shot hides depth errors — floating-vs-resting, behind-vs-in-front. A real case: chain links looked correctly attached from the front and were not attached at all when seen from the side.
Like every tool here it is a one-shot headless run: no add-on, no daemon, no socket.
9. General-Purpose Primitives (blender_locate & blender_run_script)
blender_locate: Resolves the active Blender executable on Windows, Linux, or macOS across explicit call parameters, environment variableBLENDER_EXE, standard installation paths (newest version first), and systemPATH.blender_run_script: Runs an arbitrary local Python script viablender --background --python <script.py>with optional arguments, timeout guardrail, and hard tail-buffer truncation (8 KB default, up to 50 KB max).
10. CI/CD Pipeline Integration (GitHub Actions)
Integrate headless asset QA directly into your GitHub Actions pull request checks to prevent broken FBX models, missing material slots, unapplied rotations, and displaced pivots from reaching the main branch:
name: 3D Asset QA Gate
on:
pull_request:
paths:
- "assets/**/*.fbx"
jobs:
verify-assets:
runs-on: ubuntu-latest
steps:
- name: Checkout Repository
uses: actions/checkout@v4
- name: Install Blender & Node.js
run: |
sudo snap install blender --classic
sudo apt-get install -y nodejs npm
- name: Run Headless Asset Verification
run: |
npx -y ellmos-blender-use-mcp --version
# Run structural FBX QA and 4-view visual verification
blender --background --factory-startup --python node_modules/ellmos-blender-use-mcp/scripts/verify_asset_visual.py -- \
--fbx assets/models/SM_HeroAsset.fbx \
--out build/asset-qa/ \
--json
11. Governance & Runtime Invariants
The server enforces 10 architectural and runtime invariants to guarantee privacy, safety, process isolation, and auditability:
ID | Invariant | Guarantee & Implementation Details |
| 100% Local-First & Zero Network Egress | Zero outbound network requests, external telemetry, or remote API calls. Runs fully air-gapped on the host machine. |
| Stateless & Add-on-Free Headless Execution | No Blender add-on installation, no open TCP sockets or daemon listeners, and zero mutation of the host Blender user directory. |
| Non-Elevation & Unprivileged RunAsInvoker | Operates strictly with unprivileged user-mode permissions ( |
| Strict Timeout & Tail-Buffer Bounding | Every execution is timeout-guarded. Standard output and error streams are captured into bounded tail buffers (default 8 KB, max 50 KB), preventing runaway memory. |
| Deterministic JSON & Evidence Integrity | Produces verifiable, machine-readable JSON reports containing exact mesh counts, material slots, naming prefixes, and geometry metrics. |
| Four-View Multi-Angle Visual Verification | Generates orthogonal front, side, top, and perspective renders to detect geometry defects (floating parts, unapplied rotation) that depth-blind checks miss. |
| Fail-Closed Ephemeral Staging & Script Cleanup | Ephemeral Python verification scripts and temporary staging files are unconditionally purged from the filesystem upon completion or failure. |
| Cross-Platform Operating System Parity | Uniform execution and automated discovery across Windows, Linux, and macOS without hardcoded host dependencies. |
| Cloud-Sync & Multi-Host Lock Discipline | Resilient against cloud synchronization conflicts ( |
| 48h Security Response & 5-Day Triage SLA | Formal vulnerability acknowledgment within 48 hours and triage commitment within 5 business days via official coordination channels. |
12. Security Policy & RunAsInvoker
Local Python Execution: This server runs local Python inside Blender. Use only scripts and asset paths you trust.
RunAsInvoker Non-Elevation: Runs strictly under standard unprivileged user accounts; no administrator or root privileges required.
Process Cleanup: Subprocesses are supervised; Windows processes are cleanly killed via
taskkill /pid <PID> /T /Fon timeout.Offline Assurance: No remote asset marketplaces, external APIs, or usage telemetry are involved.
Vulnerability Disclosure: Review SECURITY.md for official coordination contacts and our binding 48-hour response SLA.
13. Installation & Getting Started
Option 1: Run via npx (no install)
{
"mcpServers": {
"blender-use": {
"command": "npx",
"args": ["-y", "ellmos-blender-use-mcp"]
}
}
}Option 2: Install from source
git clone https://github.com/ellmos-ai/ellmos-blender-use-mcp.git
cd ellmos-blender-use-mcp
npm install
npm run build
node src/index.jsFor a local checkout, point command/args at the cloned src/index.js instead:
{
"mcpServers": {
"blender-use": {
"command": "node",
"args": ["<path-to-repo>/src/index.js"]
}
}
}
14. Configuration & Environment
BLENDER_EXE— optional path to the Blender executable. Without it, tools try the explicitblenderPathargument, thenBLENDER_EXE, then standard Blender install locations on Windows (%ProgramFiles%\Blender Foundation\Blender <version>\blender.exeand equivalent 32-bit and per-user roots, newest version first), thenPATH. On Linux and macOS the lookup goes straight fromBLENDER_EXEtoPATH.Every tool also accepts an explicit
blenderPathargument per call, which takes priority overBLENDER_EXE.Process output is retained only as a tail:
blender_run_scriptdefaults to 8,000 characters (configurable up to 50,000); FBX verification keeps 8,000. The response marksoutputTruncated: truewhen earlier output was discarded, so verbose Blender scripts cannot grow the MCP process memory without bound.
15. Third-Party Licenses & Level 1 SBOM
All runtime production dependencies are distributed under permissive open-source licenses (MIT and BSD-2-Clause) with 0% copyleft:
@modelcontextprotocol/sdk(MIT)update-notifier(BSD-2-Clause)zod(MIT)
For the complete dependency inventory, Invariant Cross-Reference Matrix, and prior-art isolation analysis, see THIRD_PARTY_LICENSES.md.
16. Sibling Projects & ellmos-ai Ecosystem
This MCP server is part of the ellmos-ai ecosystem — AI infrastructure, MCP servers, and intelligent tools.
MCP Server Family
Server | Tools | Focus | npm |
46 | Filesystem, process management, interactive sessions, cloud-lock-safe operations | ||
22 | Code analysis, JSON repair, imports, diffs, regex | ||
12 | File repair, format conversion, batch operations | ||
18 | n8n workflow management via AI assistants | ||
20 | MCP stack discovery, profile management, control plane | ||
45 | Local-first LLM memory, knowledge, state, routing, swarm orchestration |
| |
8 | Server operations: health checks, log analysis, deploy dry-runs, mail diagnostics |
| |
4 | Headless Blender asset QA: structural FBX reimport checks and four-view visual verification |
| |
10 | Model-agnostic computer use: capture, safety-gated actions, Windows UIA |
|
AI Infrastructure & Developer Tools
Project | Description |
Transparent command interceptor & safety sandbox for agentic workflows | |
System inspection, MCP orchestration, and fleet introspection runtime | |
High-performance episodic memory interceptor for AI agents | |
Policy distribution and compliance engine for multi-agent frameworks | |
Trust boundary verification & cryptographic token delegation authority | |
Transactional SQLite transit replication with snapshot isolation | |
Local-first text-based OS for LLM agents — 113+ handlers, 550+ tools, SQLite memory | |
Model-agnostic computer-use core powering Open Compute MCP | |
Provider-neutral LLM orchestration with auto-routing and budget tracking | |
Lightweight agent memory, connectors, and automation infrastructure | |
Self-hosted AI research stack (Ollama + n8n + Rinnsal + KnowledgeDigest) | |
Autonomous agent chain framework for Claude Code | |
Minimalist database-driven LLM OS prototype (4 functions, 1 table) | |
Testing framework for LLM operating systems (7 dimensions) |
Desktop Software Suite & Sibling Tools
Our partner organization open-bricks bundles AI-native desktop applications and developer utilities — a modern, open-source software suite built for the age of AI:
Project | Ecosystem | Description |
| Advanced file management, deep inspection, and batch pipeline workbench | |
| Unified document converter, markdown formatter, and documentation hub | |
| High-fidelity OCR processor and searchable PDF pipeline | |
| Declarative form generator and PDF schema compiler | |
| AI-assisted media categorization, tagging, and asset management | |
| Text analysis, summarization, and local language intelligence suite | |
| Knowledge extraction, semantic clustering, and synthesis engine | |
| Developer environment orchestration and multi-agent management cockpit | |
| Secure execution sandbox and isolated code-runner runtime | |
| Modular tactical game arena with automated asset pipeline validation |
17. LLM Context Index (llms.txt)
For AI assistants and LLM tooling, llms.txt provides machine-readable architecture documentation, tool descriptions, search phrases, and runtime invariants.
18. License & Statutory Disclaimer (§ 521 BGB)
License & Attribution
Distributed under the MIT License. See LICENSE and NOTICE for full copyright and attribution details.
Statutory German Disclaimer (§ 521 BGB Gefälligkeitsrecht)
This open-source package is provided free of charge without consideration (Gefälligkeit). Under statutory German law (§ 521 BGB), liability for defects in quality and title is strictly limited to intentional misconduct (Vorsatz) and gross negligence (grobe Fahrlässigkeit).
Security Response Commitment
Security vulnerabilities are triaged within 48 hours under our binding Security SLA. Refer to SECURITY.md for coordinated disclosure guidelines.
Available Tools
3 toolsblender_locateC
Resolve the local Blender executable used for background automation.
| Name | Required | Description | Default |
|---|---|---|---|
| blenderPath | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavior. It states only that the tool 'resolves' an executable, but does not explain whether it searches system paths, how it handles the optional blenderPath parameter, what happens if Blender is not found, or what the return value looks like. This lack of detail leaves significant behavioral ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, tightly worded sentence that immediately states the core purpose. It is appropriately sized and front-loaded with the key action ('Resolve'), with no wasted words or redundant detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has low complexity (one optional parameter, no output schema), making it feasible for the description to be complete. However, it omits crucial details: what the parameter does, what the tool returns, and error behavior. While the purpose is clear, the description is too skeletal for an agent to invoke the tool correctly in a real workflow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema contains one parameter, blenderPath, with no description in the schema (schema coverage 0%). The tool description does not mention this parameter at all, so it fails to explain its purpose (e.g., whether it is an override or a hint). With low schema coverage, the description must compensate, and it does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool resolves the local Blender executable, using a specific verb ('Resolve') and resource ('local Blender executable'). It distinguishes itself from siblings like blender_run_script and blender_verify_fbx_reimport by focusing on locating the executable rather than executing or verifying.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool or how it relates to the sibling tools. The phrase 'used for background automation' vaguely implies a setup/prerequisite step, but there is no mention of alternatives, exclusions, or typical workflow placement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
blender_run_scriptB
Run Blender in background mode with an explicit Python script and optional script arguments.
| Name | Required | Description | Default |
|---|---|---|---|
| cwd | No | ||
| timeoutMs | No | ||
| scriptArgs | No | ||
| scriptPath | Yes | ||
| blenderPath | No | ||
| outputTailChars | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'background mode' but does not disclose potential side effects, output handling, error behavior, timeout implications, or whether the script execution is blocking. This is insufficient for a tool that runs arbitrary scripts and could have significant side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that conveys the core functionality without any wasted words. It is appropriately concise for the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 6 parameters, no annotations, and no output schema, the description is incomplete. It does not explain how output is returned, the meaning of timeoutMs, cwd, blenderPath, or outputTailChars, nor does it mention any constraints or side effects. The description provides only a surface-level understanding, which is inadequate for a tool with this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It only mentions 'explicit Python script' and 'optional script arguments', which loosely map to scriptPath and scriptArgs, but it completely omits cwd, timeoutMs, blenderPath, and outputTailChars. The description adds minimal meaning beyond the parameter names and fails to explain the purpose of most parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool runs Blender in background mode with an explicit Python script and optional script arguments. It specifies the action (run), the resource (Blender), and the mode (background), which distinguishes it from sibling tools like blender_locate (locating Blender) and blender_verify_fbx_reimport (verifying FBX reimport).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies its usage by saying 'Run Blender in background mode with an explicit Python script', but it does not explicitly state when to use this tool versus alternatives or provide any exclusions. There is no mention of prerequisites or conditions for use, so it remains implied rather than explicitly guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
blender_verify_fbx_reimportC
Import an FBX in headless Blender and write/read a JSON verification result.
| Name | Required | Description | Default |
|---|---|---|---|
| fbxPath | Yes | ||
| timeoutMs | No | ||
| resultPath | No | ||
| blenderPath | No | ||
| requiredPrefixes | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing side effects and runtime behavior. It mentions headless Blender and file I/O, but omits external dependencies, error cases, and what the verification result contains.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no filler, front-loading the primary action and result. It is appropriately concise for the amount of information it conveys.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a tool with five parameters, no output schema, and no annotations, yet the description is only a vague one-liner. It does not explain return values, parameter semantics, or the meaning of the verification result, making it insufficient for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention or explain any of the five parameters. Required fields like fbxPath and optional parameters like resultPath and requiredPrefixes are completely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Import') and a specific resource ('FBX in headless Blender'), and clearly indicates the JSON verification output. This distinguishes it from siblings like blender_locate and blender_run_script, which target different actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus the sibling tools, nor does it mention any alternatives or exclusions. It simply states the action without placement in a workflow.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
3 tool updates
v0.1.0-alpha.7- First observed
blender_locate - First observed
blender_run_script - First observed
blender_verify_fbx_reimport
TDQS
Scored across 3 tools
Each tool has a distinct purpose: locating the executable, running a script, and verifying FBX re-import. The only slight overlap is that verify_fbx_reimport is a specialized form of run_script, but the descriptions clarify their intended uses.
All tool names follow a consistent 'blender_<verb>...' pattern (locate, run_script, verify_fbx_reimport). The naming convention is uniform and predictable.
With only 3 tools, the set is tightly scoped to Blender automation workflows. Each tool serves a clear and necessary function, and the count is well within the expected range for a focused utility server.
The toolset covers the core workflow of locating Blender, running scripts, and verifying FBX files, but lacks generic ways to retrieve script output or handle other common Blender operations. This leaves some gaps for broader automation scenarios.
Maintenance
Related MCP Connectors
Control Unreal Engine to browse assets, import content, and manage levels and sequences. Automate…
Deterministic validation for AI-generated artifacts: JSON Schema, OpenAPI response, SQL syntax.
MCP Spec Compliance MCP — audits any MCP server.json against the official Model Context Protocol
Preflight QA for AI-agent deliverables with structured verdicts and repair guidance.
Related MCP Servers
- FlicenseAqualityCmaintenanceA headless-first Model Context Protocol server for safe, deterministic Blender automation, exposing typed tools to inspect scenes and render previews without arbitrary command execution.3-
- AlicenseAqualityCmaintenanceEnables safe, repeatable preparation of game characters in Blender through high-level MCP tools for validation, import, normalization, action renaming, and GLB export, with dry-run by default and loopback-only security.9MIT
- AlicenseAqualityCmaintenanceEnables safe, structured control of Blender on Windows via a standalone STDIO MCP server, providing seven tools to inspect scenes, list and edit materials, transform objects, add modifiers, set smooth shading, and export assets without arbitrary code execution.7Apache 2.0
- AlicenseDqualityAmaintenanceEnables Blender automation via MCP with 107 tools for complex mesh modeling, PBR texturing, UV mapping, rigging, animation, lighting, rendering, and a pre-export curing pipeline for Godot 4.x/Redot GLB export.107GPL 3.0