Execution flow analysis — reads source, finds callers.
AI agents call debug_trace to retrieve information from M3 Memory without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs static analysis of code execution flows without modifying, executing, or deleting any data. It retrieves and analyzes existing source code and caller information, which is a classic Read operation. The low severity reflects that misuse would expose code structure information but cannot alter systems or execute arbitrary operations.
From the tool's definition Tool description explicitly states it 'reads source' and 'finds callers' — these are query/analysis operations with no data modification or side effects. The prefix 'debug_' indicates diagnostic/observational intent.
Documented attack patterns abuse exactly the kind of access debug_trace gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and M3 Memory, and nothing reaches the server without passing your rules. This is the rule we recommend for debug_trace:
{
"version": "1",
"default": "deny",
"tools": {
"debug_trace": {}
}
}debug_trace is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Execution flow analysis — reads source, finds callers. It is categorised as a Read tool in the M3 Memory MCP Server, which means it retrieves data without modifying state.
Register the M3 Memory MCP server in PolicyLayer and add a rule for debug_trace: 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 M3 Memory. Nothing to install.
debug_trace is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the debug_trace 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 debug_trace. 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.
debug_trace is provided by the M3 Memory MCP server (skynetcmd/m3-memory). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from M3 Memory, 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.
43 M3 Memory tools catalogued and risk-classified — across an index of 43,000+ MCP servers.