agents_traces_list

SERVERDialogbrain SOURCEhttps://api.dialogbrain.com/mcp

Low RISK CLASS

Category Read

Parameters 81 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-saloprj-dialogbrain/agents-traces-list.md

WHAT IT DOES

What agents_traces_list does on Dialogbrain

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

Parameter	Type	Required	Description
`limit`	integer	—	Max rows per page (1–100).
`offset`	integer	—	Rows to skip for pagination. OMIT to start at row 0 (default).
`source`	string	—	Filter by trace source. Single value or comma-separated, e.g. 'agent,voice'. Values: agent / auto_reply / agentic / outreach / voice. Note: source='agent' also
`status`	string	—	Filter by status. OMIT to include all statuses.
`date_to`	string	—	ISO-8601 upper bound on created_at.
`success`	boolean	—	Filter to succeeded (true) or failed (false) runs only. OMIT to include both.
`agent_id`	integer	Yes	Agent ID to pull traces for (must belong to your workspace).
`date_from`	string	—	ISO-8601 lower bound on created_at, e.g. '2026-04-10T00:00:00Z'.

Parameters from the server's own tool schema.

RISK

Why agents_traces_list is rated Low

agents_traces_list retrieves and filters execution trace logs for debugging purposes. It supports only read filters (status, success, source, date_from/date_to, pagination) and returns data without side effects. The tool is scoped to an agent and readable by an LLM, confirming its diagnostic/observability purpose. This poses minimal risk beyond information disclosure of internal agent execution details.

From the tool's definition Tool name includes 'list' and description states 'List recent execution traces' — a read-only query operation. Returns trace metadata with no mutation capability.

Risk signalsAdmin/system-level operation

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs agents_traces_list safely

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

agents_traces_list Allowed

agents_traces_list 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": {
    "agents_traces_list": {}
  }
}

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

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

FAQ

Questions about agents_traces_list

What does the agents_traces_list tool do? +

List recent execution traces for an agent — the same data as /admin/requests, scoped to one agent and readable by an LLM. Use this when an agent call timed out, drafted the wrong response, or you want to know which tool/LLM call burned the latency. Pair with agents.trace_get for full detail on a specific trace. Filters: status, success, source (single value or comma-separated: agent,voice), date_from/date_to (ISO-8601), pagination via limit/offset. Returns returned_count, dropped_on_page (should be 0 — positive means the backend agent_id predicate let something through), and has_more. Edge case: a raw page of all-dedup-dropped rows yields returned_count=0, has_more=true; re-call with offset += limit. It is categorised as a Read tool in the Dialogbrain MCP Server, which means it retrieves data without modifying state.

What parameters does agents_traces_list accept? +

agents_traces_list accepts 8 parameters: limit, offset, source, status, date_to, success, agent_id, date_from. Required: agent_id. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on agents_traces_list? +

Register the Dialogbrain MCP server in PolicyLayer and add a rule for agents_traces_list: 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 Dialogbrain. Nothing to install.

What risk level is agents_traces_list? +

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

Can I rate-limit agents_traces_list? +

Yes. Add a rate_limit block to the agents_traces_list 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 agents_traces_list completely? +

Set action: deny in the PolicyLayer policy for agents_traces_list. 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 agents_traces_list? +

agents_traces_list is provided by the Dialogbrain MCP server (https://api.dialogbrain.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

KEEP EXPLORING

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