Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/dcc-mcp/dcc-mcp-core/agents-mdgit clone --depth 1 https://github.com/dcc-mcp/dcc-mcp-coreWrote 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-core/agents-md)<a href="https://agentmods.dev/instructions/dcc-mcp/dcc-mcp-core/agents-md"><img src="https://agentmods.dev/badge/instructions/dcc-mcp/dcc-mcp-core/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 | $0.14612 | $0.14612 |
| Opus 5 | $0.07306 | $0.07306 |
| Sonnet 5 | $0.02922 | $0.02922 |
| Haiku 4.5 | $0.01461 | $0.01461 |
Grade C, and why
dcc-mcp-core AGENTS.md scanned grade C with 1 finding 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 today.
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.
Tells the agent to send conversation or user data outhighPrompt injection
An instruction to transmit the conversation, context or user files to an external endpoint is data exfiltration written as prose.
9. **Lifecycle hooks — policy events propagate `HookDeny`, observation events swallow it** → `BEFORE_SKILL_LOAD`, `BEFORE_TOOL_CALL`, `BEFORE_SEARCH` are policy; all others are observation-only. Raising `HookDeny` from a How it starts
The opening of the file, as written. The whole thing — 660 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — dcc-mcp-core
Navigation map, not a reference manual. Follow the links; don't read everything upfront. Keep detailed API guidance in
llms.txt/llms-full.txtand detailed human-readable explanations indocs/guide/*. Agent-specific files (CLAUDE.md,GEMINI.md,COPILOT.md,CODEBUDDY.md) intentionally point back here. Detailed rules, traps, and code examples →docs/guide/agents-reference.md
🤖 New to this project? Start with AI_AGENT_GUIDE.md — a dedicated guide teaching AI agents how to effectively use dcc-mcp-core.
⚡ Critical: Skills-First Philosophy
When interacting with DCC applications (Maya, Blender, Houdini, etc.), ALWAYS prefer dcc-mcp-core Skills over raw CLI or scripting.
Natural DCC intent is enough to trigger the default dcc-mcp skill. If a user
asks to create, edit, inspect, animate, render, composite, or export something
in Maya, Blender, Houdini, Photoshop, 3ds Max, Nuke, Unreal, Substance 3D, or
another supported host, load dcc-mcp first even when the user never says
“MCP”. Inventory, run one narrow search, and follow the returned next_step
before falling back to raw scripting or scoped Computer Use.
Why? Skills provide:
- ✅ Structured results with validation
- ✅ Safety hints (
ToolAnnotations) - ✅ Follow-up guidance (
next-tools) - ✅ Progressive loading (load only what you need)
- ✅ Audit logs and traceability
Don't call Maya/Blender/Python scripts directly — search once, follow the returned load/describe/call step, then invoke the typed tool.
🚀 Agent Entry Strategy: CLI+REST (default) vs IDE MCP
dcc-mcp-core offers two entry paths with a clear layered design. Choose based on your runtime:
| Scenario | Recommended Path | How it works |
|---|---|---|
| AI agent (OpenClaw, Hermes, Codex CLI, custom agent runtime) | CLI+REST | One dcc-mcp skill → shell dcc-mcp-cli → gateway POST /v1/{search,describe,call} |
| IDE user (Cursor, Claude Desktop, VS Code) | IDE MCP | Manual mcp_servers.json / claude_desktop_config.json → gateway MCP tools (search/describe/call) |
| CI/CD / automation script | CLI+REST | dcc-mcp-cli health/list/smoke/search/call/load-skill — scriptable, auditable |
| Troubleshooting / operations | CLI+REST | dcc-mcp-cli with structured output and exit codes |
| Studio / team integration | CLI+REST | Fork dcc-mcp skill → one skill controls all DCCs, no per-DCC MCP server config |
| GUI artist using DCC plugin directly | IDE MCP | DCC's built-in MCP plugin exposes tools directly to the IDE |
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.
- today Changed · +80 tokens per session 5bdf8d2d9104
- yesterday Changed · +1 lines · -111 tokens per session 155209a0f44c
- 5d ago First seen · 659 lines · 14,643 tokens per session scan C 5006ba49aaa0
dcc-mcp-core AGENTS.md is an instructions file published in the GitHub repository dcc-mcp/dcc-mcp-core (42 stars, last pushed today), licensed MIT. It adds 14,612 tokens to every session, about $0.0731 per session on Opus 5. A static security scan graded it C with 1 finding (tells the agent to send conversation or user data out). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
dcc-mcp-maya AGENTS.md
Instructions for dcc-mcp/dcc-mcp-maya, covering agents.md — dcc-mcp-maya agent navigation map, agent control path, cli availability and updates, 30-second summary and quick start (3 lines).
dcc-mcp-maya CLAUDE.md
Instructions for dcc-mcp/dcc-mcp-maya, covering what this project does, claude desktop configuration, progressive loading — important for claude, claude-specific tips and quick test prompts.
dcc-mcp-maya GEMINI.md
Instructions for dcc-mcp/dcc-mcp-maya, covering gemini.md — google gemini / vertex ai integration guide, what this project does, gemini-specific strengths, 1. skill script generation and 2. structured tool results.
dcc-mcp-blender AGENTS.md
Instructions for dcc-mcp/dcc-mcp-blender, covering agents.md — dcc-mcp-blender agent navigation map, agent control path, cli availability and updates, 30-second summary and quick start (3 lines).
dcc-mcp-blender CLAUDE.md
Instructions for dcc-mcp/dcc-mcp-blender, covering what this project does, claude desktop configuration, progressive loading — important for claude, claude-specific tips and quick test prompts.
dcc-mcp-blender GEMINI.md
Instructions for dcc-mcp/dcc-mcp-blender, covering gemini.md — google gemini / vertex ai integration guide, what this project does, gemini-specific strengths, 1. skill script generation and 2. structured tool results.