Test your MCP server or API against a stand-in consumer agent in CI
CATT runs a surrogate consumer agent against your MCP server, app or API; you define starting conditions, approvals and success conditions, and it checks the outcome on the service side.
Source
botacode on Hacker News · 2026-10-22 · Project link
Written in our own words. Credit to the original author. Link checked 2026-10-23.
What they did
CATT runs a surrogate consumer agent against your MCP server, app or API; you define starting conditions, approvals and success conditions, and it checks the outcome on the service side.
Result (as claimed)
Agent tests become repeatable despite agent memory and account state.
Tools they used
Cost: Pricing depends on the tools you pick; check each official pricing page.
Set it up
Pick a contained repo or task
Start on a branch or side project where mistakes are cheap.
Install and configure
Set up CATT, MCP. Read what it can run on your machine and limit permissions where possible.
Run it on a real task
Give it a well-scoped issue and let it work. Review the diff like any pull request.
Add guardrails
Keep tests and CI in the loop, and never let an agent push to main or touch production secrets unattended.
Copy the full setup prompt
Paste into your agent and it will walk you through the setup, asking before anything that sends, posts or spends.
You are helping me set up this AI use case end to end in Claude Code. Goal: Test your MCP server or API against a stand-in consumer agent in CI What the original author did: CATT runs a surrogate consumer agent against your MCP server, app or API; you define starting conditions, approvals and success conditions, and it checks the outcome on the service side. Reported result (as claimed by the author): Agent tests become repeatable despite agent memory and account state. Source: https://news.ycombinator.com/item?id=50201860 Tools they used: CATT, MCP Category: Dev & ops Please: 1. Ask me 3 short questions about my situation (accounts I have, budget, what I want the output to look like). 2. Propose a step-by-step plan using these tools or cheaper alternatives, with the time and cost of each step. Use official pricing pages; say "check pricing" if unsure. 3. Then do the setup with me one step at a time, waiting for my OK before anything that sends messages, posts publicly, spends money or deletes data. 4. Finish with a checklist to run it again next time.
You are helping me set up this AI use case end to end in Codex. Goal: Test your MCP server or API against a stand-in consumer agent in CI What the original author did: CATT runs a surrogate consumer agent against your MCP server, app or API; you define starting conditions, approvals and success conditions, and it checks the outcome on the service side. Reported result (as claimed by the author): Agent tests become repeatable despite agent memory and account state. Source: https://news.ycombinator.com/item?id=50201860 Tools they used: CATT, MCP Category: Dev & ops Please: 1. Ask me 3 short questions about my situation (accounts I have, budget, what I want the output to look like). 2. Propose a step-by-step plan using these tools or cheaper alternatives, with the time and cost of each step. Use official pricing pages; say "check pricing" if unsure. 3. Then do the setup with me one step at a time, waiting for my OK before anything that sends messages, posts publicly, spends money or deletes data. 4. Finish with a checklist to run it again next time.
You are helping me set up this AI use case end to end in Grok Bot. Goal: Test your MCP server or API against a stand-in consumer agent in CI What the original author did: CATT runs a surrogate consumer agent against your MCP server, app or API; you define starting conditions, approvals and success conditions, and it checks the outcome on the service side. Reported result (as claimed by the author): Agent tests become repeatable despite agent memory and account state. Source: https://news.ycombinator.com/item?id=50201860 Tools they used: CATT, MCP Category: Dev & ops Please: 1. Ask me 3 short questions about my situation (accounts I have, budget, what I want the output to look like). 2. Propose a step-by-step plan using these tools or cheaper alternatives, with the time and cost of each step. Use official pricing pages; say "check pricing" if unsure. 3. Then do the setup with me one step at a time, waiting for my OK before anything that sends messages, posts publicly, spends money or deletes data. 4. Finish with a checklist to run it again next time.
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Guides for this use case
How to build an MCP server for AI agents · How to make AI agents ask for approval before they act
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