cursorrules

Coding rules for Streamfog MCP, a bridge that lets tools control augmented-reality effects, face filters, and virtual avatars in a live OBS broadcast.

In plain words
What is it for?
Checking bridge health, listing or changing stream lenses, clearing effects, toggling an avatar, and developing the related Python and React code.
Why use it?
They document the required checks and project conventions so changes do not target the wrong effect, break the bridge, or expose environment secrets.

Cursor rule for Cursor

Install

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.

agentmods
npx agentmods add rules/sandraschi/streamfog-mcp/cursorrules
Clone the repo
git clone --depth 1 https://github.com/sandraschi/streamfog-mcp

Made for: Cursor.

Per session 269 This file is loaded in full into every session.
When invoked 269 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00269 $0.00269
Opus 5 $0.00134 $0.00134
Sonnet 5 $0.00054 $0.00054
Haiku 4.5 $0.00027 $0.00027

Measured yesterday against content hash 9417ce1f080c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 yesterday.

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.

.cursorrules · 26 lines

What it actually says

Streamfog MCP - Cursor rules

Session Context (Streamfog MCP)

You can control Streamfog AR lenses, face filters, and Vtuber avatars on the live OBS stream via the Streamer.bot bridge (5 MCP tools: streamfog_status, streamfog_set_lens, streamfog_clear_effects, streamfog_toggle_avatar, streamfog_list_lenses).

Before starting work:

  1. Check bridge health: streamfog_status()
  2. List available lenses: streamfog_list_lenses()

At end of work, save state:

  • Confirm the last dispatched action resolved to the intended lens or effect
  • If lenses.json was edited, reload with streamfog_list_lenses(reload=True)

Coding rules

  • Python: ruff (line-length 120), type hints on all public functions
  • FastMCP tools live in src/streamfog_mcp/tools/; register via @mcp.tool()
  • REST endpoints live in src/streamfog_mcp/server.py (FastAPI gateway)
  • Ports: backend 10994, frontend 10995 (fleet registry - never change)
  • Frontend: React + Vite + Tailwind + Zustand; run biome check src/
  • Never bundle .env into builds - only .env.example
Changes

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.

  1. yesterday First seen · 26 lines · 269 tokens per session scan A 9417ce1f080c

Subscribe to this mod's changes

cursorrules is a cursor rule published in the GitHub repository sandraschi/streamfog-mcp (1 stars, last pushed yesterday), licensed MIT. It adds 269 tokens to every session, about $0.0013 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.