AI agents invoke replay_stop to trigger actions in TradingView MCP Bridge. 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 executes a command that changes the state of the TradingView application—specifically halting a replay session and switching back to realtime mode. This is an Execute category action because it triggers an external operation whose effects depend on the current state of the application. While reversible (replay can be restarted), it is not merely a Read operation.
From the tool's definition Tool performs a state-changing action 'Stop replay and return to realtime' on TradingView Desktop via Chrome DevTools Protocol. It is an operational trigger that modifies the application's active mode.
Documented attack patterns abuse exactly the kind of access replay_stop gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and TradingView MCP Bridge, and nothing reaches the server without passing your rules. This is the rule we recommend for replay_stop:
{
"version": "1",
"default": "deny",
"tools": {
"replay_stop": {
"limits": [
{
"counter": "replay_stop_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} replay_stop stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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Stop replay and return to realtime. It is categorised as a Execute tool in the TradingView MCP Bridge MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the TradingView MCP Bridge MCP server in PolicyLayer and add a rule for replay_stop: 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 TradingView MCP Bridge. Nothing to install.
replay_stop 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 replay_stop 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 replay_stop. 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.
replay_stop is provided by the TradingView MCP Bridge MCP server (tradesdontlie/tradingview-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 78 TradingView MCP Bridge tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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78 TradingView MCP Bridge tools catalogued and risk-classified — across an index of 42,500+ MCP servers.