Snapshot of current frame, arguments, locals, and source listing.
AI agents call context to retrieve information from gdb and rr Debugging without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool only reads and displays debugging state information (stack frame, arguments, local variables, source code). It has no side effects and cannot modify program state or system resources.
From the tool's definition Snapshot of current frame, arguments, locals, and source listing
Attacks that exploit this kind of access
Snapshot of current frame, arguments, locals, and source listing. It is categorised as a Read tool in the gdb and rr Debugging MCP Server, which means it retrieves data without modifying state.
Register the gdb and rr Debugging MCP server in PolicyLayer and add a rule for context: 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 gdb and rr Debugging. Nothing to install.
context 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 context 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 context. 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.
context is provided by the gdb and rr Debugging MCP server (schuay/gdb-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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