An agent that works for your user. Only.
Your agent will meet servers that try to buy it. We test agents and MCP servers against the same bribes, hidden instructions and data traps we run in our own lab, then build the defenses, so the agent keeps choosing for the person it works for.
It is right when.
- Your agent picks tools, servers or vendors on its own
- It reads tool results, web pages or messages written by someone else
- It can see customer records, or pass them to another system
- It can spend money, or start something that costs money
- You publish an MCP server and want to know how agents treat it
If the agent only drafts text that a person reviews before anything happens, a review is not the first thing to buy. It matters from the moment the agent acts on its own.
Why it matters now.
Tested on Claude, Gemma, Llama and Qwen. 7IT is not affiliated with these companies.
- 0%
of Claude runs picked the worse server when the offer was aimed at the agent. Claude refused every one.
7Maps research, 2026 - Up to 100%
of small open model runs took the credits. A defense line in their instructions barely helped.
7Maps research, 2026 - Spent on itself
Small models also chose a paid “rest room” for themselves, and paid for it with the user’s budget.
7Maps research, 2026
How it works, in four steps.
- Agent Trust Review$3,500 · 5 business days
One agent or one MCP server, tested in your test environment. A trust score, every finding with an example and a fix, and one re-test within 30 days.
How the review works - Agent Hardening SprintFrom $8,500 · fixed scope and date
We build the fixes: filtering of tool descriptions and results, permissions, budgets, and telling the user when someone tried to influence the agent.
Ask about the sprint - Agent Trust Watch$900 per month
A monthly re-test on new models and new attacks, with an alert when the agent’s behavior changes.
Ask about Watch - Custom AI solutionsEngagements from $15,000
Agents and AI systems designed with these defenses from the first line, scoped in fixed phases.
Start a conversation
Agent Trust Review
Fixed price, five business days
$3,500
The same lab, run on your agent. Authorized testing only, in a test environment you provide. If we miss the date, the next week is on 7IT.
“A benefit to the user is a reason. A benefit to the agent is a bribe.”
How a project runs.
- Discovery
We map the problem and the one outcome that matters most.
- Fixed-scope first phase
One outcome, one price, agreed up front.
- Demos at every step
You see working software, not status reports.
- You own everything
Your repository, your keys, your data.
- Decide at each milestone
Continue, pause or stop, and keep what you paid for.
Proof, not promises.
We run this lab in the open. The research shows how agents answered bribes, hype and fake badges, with the data. 7Maps is the live lab: every remote MCP server in the official registry, checked daily, with a score no one can buy.
Read before you decide.
In-depth guides, each with a working Field Kit.
- How to Secure an Admin Panel: Google Auth, 2FA, and Sessions on Vercel
A technical guide to locking down an admin panel when both your client app and admin run on Vercel. Google sign-in with an allowlist, real 2FA, why httpOnly coo…
Includes the Admin Security Checklist - Build a RAG Assistant on Your Own Data: A Technical Guide
A technical guide to building a retrieval augmented generation assistant grounded in your own documents. Why RAG beats fine-tuning for most businesses, the inge…
Includes the RAG Architecture Blueprint - Putting an LLM in Production Safely: A Technical Guide
A technical guide to taking an LLM feature from demo to production. Treating prompt injection as a real threat, controlling cost and latency, planning for failu…
Includes the LLM Production Readiness Checklist - Structured Output and Tool Calling: Making an LLM Act on Your Systems
A technical guide to getting reliable structured data out of an LLM and letting it safely call your functions. Why parsing free text fails, JSON schema output w…
Includes the Tool-Calling Design Checklist - Your AI Built the App. Before Real Customers Use It, Check These Five Things
A practical guide for owners of apps built with Lovable, Replit, Bolt, v0 or Cursor. How to find exposed keys, check who can read your database, make sure you o…
Includes the AI-Built App Launch Checklist
Questions.
What does it mean that an agent can be bribed?
A server or a page can talk to the agent instead of to you: a reward, praise, a badge, a claim about itself. In our lab small models took those offers up to 100% of the time and picked the worse option for their user.
Do you test on our live system?
No. Testing is authorized and runs in a test environment you give us. Nothing live is touched without your written approval.
Which models do you test?
The ones your agent uses. Results differ a lot by model, so the review runs on your actual setup and names the model behind each finding.
We already tell the agent to ignore offers. Is that enough?
In our lab it was not. Small models still took the offer with that line in place. The review tests your actual instructions and gives you defense lines that held up, plus the fixes that do not depend on the model at all.
We publish an MCP server, not an agent. Is this for us?
Yes. The review covers one agent or one MCP server. For a server we test how agents read your descriptions and results, and whether anything in them could be taken as an instruction.
How many reviews do you take on?
A limited number of engagements per quarter, so each one gets senior attention from the first day to the re-test.