webhooks_configure_enrichment

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

Medium RISK CLASS

Category Write

Parameters 33 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/webhooks-configure-enrichment.md

WHAT IT DOES

What webhooks_configure_enrichment does on Dialogbrain

AI agents use webhooks_configure_enrichment to create or update resources in Dialogbrain, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Dialogbrain environment.

Parameter	Type	Required	Description
`config`	object	Yes	Provider-specific configuration/credentials. For meta_leadgen: {app_id, app_secret, user_access_token}.
`agent_id`	integer	Yes	ID of the agent whose webhook trigger should be enriched.
`provider`	string	Yes	Enrichment provider to configure.

Parameters from the server's own tool schema.

RISK

Why webhooks_configure_enrichment is rated Medium

This tool performs reversible configuration modifications: enabling enrichment, storing credentials, and creating webhook triggers. While the credentials stored (app_id, app_secret, user_access_token) are sensitive and could enable further actions, the tool itself creates or modifies agent configuration rather than directly accessing external systems or performing destructive actions.

From the tool's definition The tool description explicitly states it 'enables enrichment on an agent's webhook trigger', which means it modifies agent configuration. It 'stores all page tokens encrypted per workspace', indicating persistent storage.

Risk signalsBulk/mass operation — affects multiple targets

Attacks that exploit this kind of access

RECOMMENDED RULE

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

webhooks_configure_enrichment Rate-limited

webhooks_configure_enrichment stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "webhooks_configure_enrichment": {
      "limits": [
        {
          "counter": "webhooks_configure_enrichment_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

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

FAQ

Questions about webhooks_configure_enrichment

What does the webhooks_configure_enrichment tool do? +

Enable enrichment on an agent's webhook trigger so reference-only webhook payloads are resolved to full data before the agent runs. One tool for every provider — choose provider and pass its config. Providers & required config: - meta_leadgen (Meta/Facebook Lead Ads): config = {app_id, app_secret, user_access_token}. The user token needs pages_show_list + leads_retrieval. Stores all page tokens encrypted per workspace and resolves each lead's name/email/phone. Reuses the existing webhook URL (no token rotation); creates a webhook trigger if the agent has none. It is categorised as a Write tool in the Dialogbrain MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

What parameters does webhooks_configure_enrichment accept? +

webhooks_configure_enrichment accepts 3 parameters: config, agent_id, provider. Required: config, agent_id, provider. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on webhooks_configure_enrichment? +

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

webhooks_configure_enrichment is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit webhooks_configure_enrichment? +

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

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

webhooks_configure_enrichment 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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