Execute all test cases in a project via FastAPI to ensure executions are tracked.
AI agents invoke run_project to trigger actions in OpenTester. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool runs test cases whose behavior depends on the content of the project—it executes code through a testing framework (FastAPI-based). While the primary purpose is testing (not arbitrary code execution), the actual effects depend on what test cases are defined in the project. This fits Execute category as it triggers external operations (test execution) with argument-dependent side effects.
From the tool's definition Tool description states 'Execute all test cases in a project' and the server description indicates it 'provides a unified DSL format and MCP interface, enabling Agents to generate, execute, and manage test cases'.
Documented attack patterns abuse exactly the kind of access run_project gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and OpenTester, and nothing reaches the server without passing your rules. This is the rule we recommend for run_project:
{
"version": "1",
"default": "deny",
"tools": {
"run_project": {
"limits": [
{
"counter": "run_project_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}run_project stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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Execute all test cases in a project via FastAPI to ensure executions are tracked. It is categorised as a Execute tool in the OpenTester MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the OpenTester MCP server in PolicyLayer and add a rule for run_project: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches OpenTester. Nothing to install.
run_project is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the run_project rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for run_project. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
run_project is provided by the OpenTester MCP server (kznr02/opentester). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from OpenTester, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
23 OpenTester tools catalogued and risk-classified — across an index of 43,000+ MCP servers.