Reload launch.json from current project and return available debug configurations.
AI agents call refresh_debug_targets to retrieve information from Openocd without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs a read operation: it reloads a configuration file and returns the available debug configurations. There are no side effects that create, modify, delete, or execute anything. The action is purely informational retrieval. Severity is low because misuse would only expose configuration metadata without affecting running systems or data integrity.
From the tool's definition Tool description states 'Reload launch.json from current project and return available debug configurations' — it reads and returns configuration data without modifying state or triggering execution.
Documented attack patterns abuse exactly the kind of access refresh_debug_targets gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Openocd, and nothing reaches the server without passing your rules. This is the rule we recommend for refresh_debug_targets:
{
"version": "1",
"default": "deny",
"tools": {
"refresh_debug_targets": {}
}
}refresh_debug_targets is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Reload launch.json from current project and return available debug configurations. It is categorised as a Read tool in the Openocd MCP Server, which means it retrieves data without modifying state.
Register the Openocd MCP server in PolicyLayer and add a rule for refresh_debug_targets: 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 Openocd. Nothing to install.
refresh_debug_targets 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 refresh_debug_targets 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 refresh_debug_targets. 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.
refresh_debug_targets is provided by the Openocd MCP server (luiox/openocd-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Openocd, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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14 Openocd tools catalogued and risk-classified — across an index of 43,000+ MCP servers.