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 rules/sandraschi/ai-producer-hub/cursorrulesgit clone --depth 1 https://github.com/sandraschi/ai-producer-hubWrote 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/rules/sandraschi/ai-producer-hub/cursorrules)<a href="https://agentmods.dev/rules/sandraschi/ai-producer-hub/cursorrules"><img src="https://agentmods.dev/badge/rules/sandraschi/ai-producer-hub/cursorrules.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 | $0.00352 | $0.00352 |
| Opus 5 | $0.00176 | $0.00176 |
| Sonnet 5 | $0.00070 | $0.00070 |
| Haiku 4.5 | $0.00035 | $0.00035 |
Grade A, and why
cursorrules 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 6d 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.
What it actually says
AI Producer Hub - Cursor Rules
Project Overview
Composite MCP server for AI-powered music production workflows. Mounts and orchestrates multiple MCP servers (VirtualDJ, Plex, Suno, Reaper, OBS).
Architecture
server.py: Main FastMCP server with workflow toolstools/midi.py: MIDI input/output tools- Mounts other MCP servers at prefixed paths (/dj/, /plex/, etc.)
Tool Patterns
- All tools use
@mcp.tool()decorator - MIDI tools registered via
setup_midi_tools(mcp)pattern - Workflow tools return framework_ready status when dependencies unavailable
Mounted Servers
/dj/*- VirtualDJ-MCP (mixing, stems, 8 decks)/plex/*- Plex-MCP (media library)/suno/*- Suno-MCP (AI generation)/reaper/*- Reaper-MCP (DAW)/obs/*- OBS-MCP (streaming)
Code Style
- Use Rich console for stderr output (not stdout)
- Async/await for all tool implementations
- Type hints required
- Docstrings with Args/Returns sections
Key Workflows
- suno_to_deck: Generate AI track -> Load to DJ deck
- ai_dj_set: Generate multiple tracks -> Auto-mix
- live_stream_producer: Generate + Mix + Stream live
- album_factory: Theme -> Full album -> Plex
Dependencies
- fastmcp>=2.13.0
- rich (for console output)
- python-rtmidi, mido (optional, for MIDI)
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.
- 6d ago First seen · 41 lines · 352 tokens per session scan A 05d3cb9ddf23
cursorrules is a cursor rule published in the GitHub repository sandraschi/ai-producer-hub (5 stars, last pushed 5d ago), licensed MIT. It adds 352 tokens to every session, about $0.0018 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 2026-08-31.
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