[CodeLoop] You MUST call codeloop_verify after every code change. If .codeloop/config.json is missing, call codeloop_init_project FIRST. Stop a background recording that was started with codeloop_start_recording. The video file is finalized, app logs are saved, the IDE/agent window is restored t...
Bulk/mass operation — affects multiple targets
Part of the Codeloop MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents invoke codeloop_stop_recording to trigger processes or run actions in Codeloop. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.
codeloop_stop_recording can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. Intercept enforces rate limits and validates arguments to keep execution within safe bounds.
Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.
tools:
codeloop_stop_recording:
rules:
- action: allow
rate_limit:
max: 10
window: 60
validate:
required_args: true See the full Codeloop policy for all 29 tools.
Agents calling execute-class tools like codeloop_stop_recording have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Execute risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.
codeloop_stop_recording is one of the high-risk operations in Codeloop. For the full severity-focused view — only the high-risk tools with their recommended policies — see the breakdown for this server, or browse all high-risk tools across every MCP server.
[CodeLoop] You MUST call codeloop_verify after every code change. If .codeloop/config.json is missing, call codeloop_init_project FIRST. Stop a background recording that was started with codeloop_start_recording. The video file is finalized, app logs are saved, the IDE/agent window is restored to the front, and the video path is returned. After stopping, call codeloop_interaction_replay with the run_id to extract frames and analyze the captured flow. The response includes log_path if app logs were captured during the recording session.. It is categorised as a Execute tool in the Codeloop MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Add a rule in your Intercept YAML policy under the tools section for codeloop_stop_recording. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Codeloop MCP server.
codeloop_stop_recording 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 codeloop_stop_recording rule in your Intercept 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 Intercept policy for codeloop_stop_recording. 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.
codeloop_stop_recording is provided by the Codeloop MCP server (codeloop-mcp-server). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic policy on every MCP tool call. Per-identity grants. Full audit log.