Returns the user provided launch configuration along with its detailed schema for a DAP-compatible debugger. The schema includes descriptions for each field.
AI agents call get_launch_config to retrieve information from Dap without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and returns existing configuration data without side effects. It is a read-only operation that retrieves configuration metadata and schema information. While it may expose sensitive details about debugger setup, the tool itself performs no destructive, executable, or financial actions.
From the tool's definition Tool name is 'get_launch_config' and description states it 'Returns the user provided launch configuration' — a retrieval operation with no modification, deletion, or execution of code.
Documented attack patterns abuse exactly the kind of access get_launch_config gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Dap, and nothing reaches the server without passing your rules. This is the rule we recommend for get_launch_config:
{
"version": "1",
"default": "deny",
"tools": {
"get_launch_config": {}
}
}get_launch_config is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Returns the user provided launch configuration along with its detailed schema for a DAP-compatible debugger. The schema includes descriptions for each field. It is categorised as a Read tool in the Dap MCP Server, which means it retrieves data without modifying state.
Register the Dap MCP server in PolicyLayer and add a rule for get_launch_config: 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 Dap. Nothing to install.
get_launch_config 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 get_launch_config 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 get_launch_config. 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.
get_launch_config is provided by the Dap MCP server (kashuncheng/dap_mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Dap, 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 Dap tools catalogued and risk-classified — across an index of 43,000+ MCP servers.