agents_get
Get detailed information about a specific AI agent. Returns full agent config including: - Execution configuration - Tool configuration - Knowledge configuration - Escalation configuration - Triggers list - Knowledge collections - Custom AI instructions (prompt_text) - Auto-reply rules override (...
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What agents_get does on Dialogbrain
AI agents call agents_get 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 |
|---|---|---|---|
agent_id | integer | Yes | ID of the AI agent to fetch |
Parameters from the server's own tool schema.
Why agents_get is rated Low
This is a Read operation—it queries and retrieves agent configuration data without modifying, deleting, or executing anything. The severity is medium rather than low because the returned information includes execution configuration, custom AI instructions, and escalation rules that could be sensitive or enable social engineering if exposed to an unauthorized agent.
From the tool's definition Tool retrieves and returns 'detailed information about a specific AI agent' including configuration data, knowledge, instructions, and rules. The verb 'Get' and the passive 'Returns' indicate data retrieval with no modification.
Attacks that exploit this kind of access
The rule that runs agents_get 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_get, this is the rule to start with:
agents_get is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Dialogbrain, apply this rule, and every agents_get call is checked against it from then on.
Questions about agents_get
Get detailed information about a specific AI agent. Returns full agent config including: - Execution configuration - Tool configuration - Knowledge configuration - Escalation configuration - Triggers list - Knowledge collections - Custom AI instructions (prompt_text) - Auto-reply rules override (auto_reply_rules). It is categorised as a Read tool in the Dialogbrain MCP Server, which means it retrieves data without modifying state.
agents_get accepts 1 parameter: agent_id. Required: agent_id. The full parameter table on this page comes from the server's own tool schema.
Register the Dialogbrain MCP server in PolicyLayer and add a rule for agents_get: 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.
agents_get 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 agents_get 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 agents_get. 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.
agents_get 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.
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