AI agents invoke sessions_continue to trigger actions in Debug-MCP. 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 resumes execution of a Python debugging session, triggering code to run until the next breakpoint. It falls under Execute because it directly triggers external code execution. Severity is medium since it operates within a controlled debug session, but misuse could cause unintended code paths to run.
From the tool's definition 'Continue execution to the next breakpoint' — resumes running code in a debug session
Attacks that exploit this kind of access
Continue execution to the next breakpoint. It is categorised as a Execute tool in the Debug-MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Debug- MCP server in PolicyLayer and add a rule for sessions_continue: 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 Debug-MCP. Nothing to install.
sessions_continue 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 sessions_continue 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 sessions_continue. 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.
sessions_continue is provided by the Debug- MCP server (kaina3/debug-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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