Borrowing it
Nothing to install: this file belongs to dcc-mcp/dcc-mcp-blender. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/dcc-mcp/dcc-mcp-blender/main/AGENTS.mdgit clone --depth 1 https://github.com/dcc-mcp/dcc-mcp-blenderWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/dcc-mcp/dcc-mcp-blender/agents-md)<a href="https://agentmods.dev/instructions/dcc-mcp/dcc-mcp-blender/agents-md"><img src="https://agentmods.dev/badge/instructions/dcc-mcp/dcc-mcp-blender/agents-md.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.01555 | $0.01555 |
| Opus 5 | $0.00777 | $0.00777 |
| Sonnet 5 | $0.00311 | $0.00311 |
| Haiku 4.5 | $0.00155 | $0.00155 |
Grade A, and why
dcc-mcp-blender AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — dcc-mcp-blender Agent Navigation Map
Progressive disclosure: this file is a map, not an encyclopedia. Follow the links for depth. Stay here for breadth.
Agent Control Path
AI agent runtimes default to the shared gateway through the
dcc-mcp skill and dcc-mcp-cli REST commands:
dcc-mcp-cli search --query "<task>" --dcc-type blender
dcc-mcp-cli describe <tool-slug>
dcc-mcp-cli call <tool-slug> --json '{"key":"value"}'
Use dcc-mcp-cli list for live instances and dcc-mcp-cli dcc-types for
release-catalog support. IDE users may continue to configure the gateway MCP
endpoint; adapter-local Python start APIs are for host bootstrap and tests.
CLI availability and updates
If dcc-mcp-cli is missing, obtain user consent before using the official
install commands in the README Agent workflow. Keep an official build current
with:
dcc-mcp-cli update check
dcc-mcp-cli update apply
update apply stages the latest CLI for the next launch; it does not replace
a running server.
30-Second Summary
dcc-mcp-blender embeds a standards-compliant MCP Streamable HTTP server directly inside Blender. It exposes 200+ Blender operations as MCP tools that any AI agent (Claude, Gemini, Cursor, etc.) can call over HTTP — no external gateway, no subprocess bridge.
Current version: 0.1.20
Core dependency: dcc-mcp-core>=0.20.0,<1.0.0
Python: 3.10+ (bundled with Blender)
Blender: 3.6 LTS, 4.2 LTS, 4.3, 4.4
Quick Start (3 Lines)
import dcc_mcp_blender
handle = dcc_mcp_blender.start_server()
# MCP client connects through http://127.0.0.1:9765/mcp
Or install the Blender extension (ZIP) and the server starts automatically.
Information Layers — Pick Your Depth
Layer 1 — You Are a User / Operator
Goal: Install, configure, and connect an MCP host.
- README.md — Installation, quick start, environment variables, bundled tools list.
- install.md — Agent-facing setup entry: install pip dependencies, guide Blender add-on loading, and run a first smoke prompt.
- skills/dcc-mcp-blender-setup/SKILL.md — Setup skill reference, one-command install script.
- src/dcc_mcp_blender/skills/SKILLS_INDEX.md — Staged loading guidance, task-to-skill chains, side-effect profiles for all bundled skills.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 133 lines · 1,555 tokens per session scan A 85491c054bf1
dcc-mcp-blender AGENTS.md is an instructions file published in the GitHub repository dcc-mcp/dcc-mcp-blender (28 stars, last pushed yesterday), licensed MIT. It adds 1,555 tokens to every session, about $0.0078 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.