Executes a CloudWatch Logs Insights query and waits for the results to be available. IMPORTANT: The operation must include exactly one of the following parameters: log_group_names, or log_group_identifiers. CRITICAL: The volume of returned logs can easily overwhelm the agent context window. Alw...
Part of the AWS Labs CloudWatch MCP Server MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents invoke execute_log_insights_query to trigger processes or run actions in AWS Labs CloudWatch MCP Server. 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.
execute_log_insights_query 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:
execute_log_insights_query:
rules:
- action: allow
rate_limit:
max: 10
window: 60
validate:
required_args: trueSee the full AWS Labs CloudWatch MCP Server policy for all 19 tools.
Agents calling execute-class tools like execute_log_insights_query 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.
execute_log_insights_query is one of the high-risk operations in AWS Labs CloudWatch MCP Server. 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.
Executes a CloudWatch Logs Insights query and waits for the results to be available. IMPORTANT: The operation must include exactly one of the following parameters: log_group_names, or log_group_identifiers. CRITICAL: The volume of returned logs can easily overwhelm the agent context window. Always include a limit in the query (| limit 50) or using the limit parameter. Usage: Use to query, filter, collect statistics, or find patterns in one or more log groups. For example, the following query lists exceptions per hour. ``` filter @message like /Exception/ | stats count(*) as exceptionCount by bin(1h) | sort exceptionCount desc ``` Returns: -------- A dictionary containing the final query results, including: - status: The current status of the query (e.g., Scheduled, Running, Complete, Failed, etc.) - results: A list of the actual query results if the status is Complete. - statistics: Query performance statistics - messages: Any informational messages about the query. It is categorised as a Execute tool in the AWS Labs CloudWatch MCP Server 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 execute_log_insights_query. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the AWS Labs CloudWatch MCP Server MCP server.
execute_log_insights_query 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 execute_log_insights_query 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 execute_log_insights_query. 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.
execute_log_insights_query is provided by the AWS Labs CloudWatch MCP Server MCP server (awslabs.cloudwatch-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.