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 agents/orangeproai/orangepro-mcp/cursorgit clone --depth 1 https://github.com/OrangeproAI/orangepro-mcpWhat 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 | $0.00000 | $0.00416 |
| Opus 5 | $0.00000 | $0.00208 |
| Sonnet 5 | $0.00000 | $0.00083 |
| Haiku 4.5 | $0.00000 | $0.00042 |
Grade A, and why
cursor 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 2d 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
OrangePro With Cursor
Install
npm install -g @orangepro/orangepro-mcp
cd /path/to/your/repo
opro
The first opro run creates .orangepro/behavior-coverage.html, .orangepro/rtm.md, and an agent-ready plan. With a configured model key, weak AI grounding and AI-suggested candidate flows are applied automatically and stay out of Proven coverage.
Cursor Plugin
Install OrangePro from the Cursor Marketplace when it is listed. Until then, use the bundled plugin directory for local testing:
plugins/orangepro
The plugin starts the orangepro-local MCP server through npx -y @orangepro/mcp-server@latest mcp and applies OrangePro rules for gap/test workflows. It does not pin a model; provider keys and model defaults come from your environment, .env.provider.local, .env.local, .env, or opro setup.
MCP Setup
Print the Cursor MCP block:
opro agent --client cursor
Paste the printed block into Cursor Settings -> MCP or ~/.cursor/mcp.json. If Cursor does not inherit your shell environment, add the provider key to the local MCP config, or keep it in a repo-local .env.provider.local file that is not committed.
If your Cursor setup supports custom commands, map /opro to: call orangepro_start for the current checkout, then follow the returned next_actions. The shortcut should use the MCP tool so Proven / Associated signal / No integration signal semantics stay intact.
Agent Prompt
Use OrangePro first. Call orangepro_start in this repo, then follow its next_actions. Generate tests with orangepro_generate_tests, write only runnable outputs with run_hints, run the suggested command, and call `orangepro_prove` with the returned `prove_run` args after a passing run for Dynamically Proven. Use record_run only for static diagnostics.
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.
- 2d ago First seen · 40 lines · 0 tokens per session scan A feca4ce7f133
cursor is an agent published in the GitHub repository OrangeproAI/orangepro-mcp (17 stars, last pushed 6d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 416 tokens. 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.
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