agent_trace

SERVERProAgentStore SOURCEhttps://mcp.proagentstore.online/mcp

Low RISK CLASS

Category Read

Parameters 00 required

Recommended Allowedsee the rule below

Registry record Grade D, identity unverified Pull the record →

This record as markdown: /tools/io-github-proagentstore-platform/agent-trace.md

WHAT IT DOES

What agent_trace does on ProAgentStore

AI agents call agent_trace to retrieve information from ProAgentStore without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

RISK

Why agent_trace is rated Low

Tool retrieves and displays agent execution history for inspection; no side effects or data modification.

From the tool's definition Reconstruct timeline, see what happened, debugging tool, no modifications

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs agent_trace safely

PolicyLayer is an MCP gateway: it sits between your AI agents and ProAgentStore, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For agent_trace, this is the rule to start with:

agent_trace Allowed

agent_trace is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "agent_trace": {}
  }
}

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect ProAgentStore, apply this rule, and every agent_trace call is checked against it from then on.

FAQ

Questions about agent_trace

What does the agent_trace tool do? +

Reconstruct the complete, time-ordered timeline of what an agent instance DID — chat turns (chat.in/tool.call/chat.out), apply steps/handoffs/outcomes (apply.*), and failures, interleaved. This is the primary tool for debugging or improving an agent: see exactly what happened, in order, not just errors. Failures sit in two bands: a tool call that FAILED is level=warn (one row per failed tool, carrying the tool name in. It is categorised as a Read tool in the ProAgentStore MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on agent_trace? +

Register the ProAgentStore MCP server in PolicyLayer and add a rule for agent_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 ProAgentStore. Nothing to install.

What risk level is agent_trace? +

agent_trace is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit agent_trace? +

Yes. Add a rate_limit block to the agent_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.

How do I block agent_trace completely? +

Set action: deny in the PolicyLayer policy for agent_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.

What MCP server provides agent_trace? +

agent_trace is provided by the ProAgentStore MCP server (https://mcp.proagentstore.online/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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