Run a guarded build command (allowlist/timeout; user_confirmed=true required) and return build result.
AI agents invoke build_project to trigger actions in DumpAnalysisMCP. 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 triggers code compilation and build system execution, which qualifies as Execute rather than Write. Although guarded by allowlist and timeout mechanisms, it still runs arbitrary build commands whose side effects (compilation, linking, artifact generation) depend on the project configuration.
From the tool's definition Tool performs 'Run a guarded build command' with timeout and allowlist controls. Executes external build system operations with effects dependent on the codebase being built.
Documented attack patterns abuse exactly the kind of access build_project gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and DumpAnalysisMCP, and nothing reaches the server without passing your rules. This is the rule we recommend for build_project:
{
"version": "1",
"default": "deny",
"tools": {
"build_project": {
"limits": [
{
"counter": "build_project_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}build_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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Run a guarded build command (allowlist/timeout; user_confirmed=true required) and return build result. It is categorised as a Execute tool in the DumpAnalysisMCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the DumpAnalysis MCP server in PolicyLayer and add a rule for build_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 DumpAnalysisMCP. Nothing to install.
build_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 build_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 build_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.
build_project is provided by the DumpAnalysis MCP server (kindtis/dumpanalysismcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from DumpAnalysisMCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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12 DumpAnalysisMCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.