agents_ask

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

High RISK CLASS

Category Execute

Parameters 32 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

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

WHAT IT DOES

What agents_ask does on Dialogbrain

AI agents invoke agents_ask to trigger actions in Dialogbrain. 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.

Parameter	Type	Required	Description
`message`	string	Yes	Message/goal to send to the agent
`agent_id`	integer	Yes	ID of the AI agent to ask
`send_mode`	string	—	Send mode for the agent run: 'draft' = create drafts, 'auto' = send directly. Defaults to the agent's configured default_send_mode. Does NOT change execution_mo

Parameters from the server's own tool schema.

RISK

Why agents_ask is rated High

This tool triggers execution of an AI agent that can invoke its own tools (including potentially send messages, run scripts, etc.), making it an Execute-category tool. The blast radius is high because the agent may chain further actions across WhatsApp, Telegram, Email, voice, and other configured tools, multiplying the effect of a single misuse.

From the tool's definition 'Send a message to an AI agent and get its response. The agent runs with its configured prompt, tools, and knowledge.' and 'tool_calls[] is the per-tool trace in call order'

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs agents_ask 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_ask, this is the rule to start with:

agents_ask Rate-limited

agents_ask 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "agents_ask": {
      "limits": [
        {
          "counter": "agents_ask_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL → Instant setup, no code required.

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

FAQ

Questions about agents_ask

What does the agents_ask tool do? +

Send a message to an AI agent and get its response. The agent runs with its configured prompt, tools, and knowledge. Use this to test agents or have them process a task. Returns: {status: 'replied'|'silent', response_text, messages[], full_reply, model_used, tokens_*, send_mode, execution_mode, tool_calls[]}. tool_calls[] is the per-tool trace in call order — each {tool, success, error, duration_ms} — so you can see which tool the agent ran and why it failed (e.g. a workbench script error) directly from this response, no trace lookup needed. messages[] carries each messages.send invocation the agent made (text, subject, reply_to_message_id, timestamp, message_id, attachments=[{file_id,name,mime}]). full_reply concatenates text only — attachment-only sends show up in messages but not full_reply. status='silent' iff both response_text is empty AND messages is empty. Execution may take 10-60s depending on agent complexity. It is categorised as a Execute tool in the Dialogbrain MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

What parameters does agents_ask accept? +

agents_ask accepts 3 parameters: message, agent_id, send_mode. Required: message, 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_ask? +

Register the Dialogbrain MCP server in PolicyLayer and add a rule for agents_ask: 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_ask? +

agents_ask is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit agents_ask? +

Yes. Add a rate_limit block to the agents_ask 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_ask completely? +

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

agents_ask 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

More on Dialogbrain, and thousands of servers like it.

This server

All 225 Dialogbrain tools → High-risk tools on this server →

Across the catalogue

All high-risk MCP tools → The MCP Attack Database →

Guides

Govern code and CI agents →Agent sandbox →Least privilege for MCP →