Retrieve trace data by trace ID from Mackerel for distributed tracing analysis. 🔍 USE THIS TOOL WHEN USERS: - Analyze performance bottlenecks in distributed systems - Investigate error propagation across microservices - Understand request flow and service dependencies - Debug latency issues and ...
AI agents call get_trace to retrieve information from Mackerel MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs a retrieval operation on distributed tracing data. It retrieves pre-existing trace information by ID for analysis and debugging purposes. No data is created, modified, deleted, or executed. The use cases explicitly describe analysis, investigation, and documentation—all read-only activities.
From the tool's definition Tool description states 'Retrieve trace data by trace ID from Mackerel' and use cases include 'Analyze performance bottlenecks', 'Investigate error propagation', 'Understand request flow', and 'Debug latency issues'.
Documented attack patterns abuse exactly the kind of access get_trace gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Mackerel MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for get_trace:
{
"version": "1",
"default": "deny",
"tools": {
"get_trace": {}
}
}get_trace is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Retrieve trace data by trace ID from Mackerel for distributed tracing analysis. 🔍 USE THIS TOOL WHEN USERS: - Analyze performance bottlenecks in distributed systems - Investigate error propagation across microservices - Understand request flow and service dependencies - Debug latency issues and identify slow operations - Generate documentation of system architecture from trace data <examples> Basic trace retrieval (first page) \. It is categorised as a Read tool in the Mackerel MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Mackerel MCP Server MCP server in PolicyLayer and add a rule for get_trace: 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 Mackerel MCP Server. Nothing to install.
get_trace 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_trace 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_trace. 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_trace is provided by the Mackerel MCP Server MCP server (mackerelio-labs/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Mackerel MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
16 Mackerel MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.