# ai_filters_create

Create a new AI filter for semantic intent-based message matching. AI filters use vector embeddings (via Voyage AI) to detect whether an incoming message matches a specific intent or topic. The filter's description is embedded as a reference vector at creation time. When a message arrives, its embedding is compared against this reference using cosine similarity. The description field is the most important part — it becomes the reference embedding that all incoming messages are compared against. Write it as a clear statement of what kind of messages should match: - 'Customer asking about pricing, subscription plans, or billing' - 'User reporting a bug, crash, or unexpected behavior in the product' - 'Inbound sales lead expressing interest in purchasing or trialing' The threshold controls sensitivity: 0.5 is a balanced default, lower values (0.3) cast a wider net, higher values (0.8) require closer matches. Note: This tool calls the Voyage AI embedding API to generate the reference vector.

Agent View of the PolicyLayer registry record for `ai_filters_create`. HTML page: https://policylayer.com/tools/io-github-saloprj-dialogbrain/ai-filters-create

## Facts

- Tool: `ai_filters_create`
- Server: Dialogbrain (`https://api.dialogbrain.com/mcp`) — https://policylayer.com/tools/io-github-saloprj-dialogbrain.md
- Homepage: https://github.com/saloprj/dialogbrain-mcp
- Risk category: Write (Medium risk)
- Registry record: grade F, identity unverified
- Server auth posture: open
- Server rate-limited: no
- Parameters: 3 (2 required)
- Recommended policy verdict: Rate-limited

## Parameters

| Parameter | Type | Required | Description |
| --- | --- | --- | --- |
| `name` | string | yes | Filter name — a short, human-readable label (max 100 chars) |
| `threshold` | number | no | Cosine similarity threshold for a message to be considered a match. Range 0.1–1.0. Default 0.50. Lower values (e.g. 0.3) are more permissive and catch more mess |
| `description` | string | yes | Reference text that defines what messages should match this filter. This text is embedded as a vector and used for cosine similarity comparison against all inco |

Parameters from the server's own tool schema.

## Example call (MCP tools/call, JSON-RPC 2.0)

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "ai_filters_create",
    "arguments": {
      "name": "<name>",
      "description": "<description>"
    }
  }
}
```

## Why ai_filters_create is rated Medium

This tool creates and stores a new semantic filter configuration that modifies how messages are processed in the unified inbox. While not destructive (the filter can be deleted), it is a write operation that persists state.

From the tool's own definition: "Tool name contains 'create' and description states 'Create a new AI filter' — this irreversibly adds a new filter configuration to the system. The filter persists and affects message routing/categorization going forward."

## Use case

AI agents use ai_filters_create 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.

## Recommended policy (PolicyLayer)

Verdict: **Rate-limited**. Enforced by the PolicyLayer MCP gateway (https://policylayer.com/mcp-gateway) before a call reaches Dialogbrain:

```json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "ai_filters_create": {
      "limits": [
        {
          "counter": "ai_filters_create_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}
```

## Other tools on Dialogbrain (224)

- `agents_delete` — Destructive — https://policylayer.com/tools/io-github-saloprj-dialogbrain/agents-delete.md
- `agents_trigger_delete` — Destructive — https://policylayer.com/tools/io-github-saloprj-dialogbrain/agents-trigger-delete.md
- `ai_filters_delete` — Destructive — https://policylayer.com/tools/io-github-saloprj-dialogbrain/ai-filters-delete.md
- `ai_tags_delete` — Destructive — https://policylayer.com/tools/io-github-saloprj-dialogbrain/ai-tags-delete.md
- `calendar_delete_event` — Destructive — https://policylayer.com/tools/io-github-saloprj-dialogbrain/calendar-delete-event.md
- `collections_delete` — Destructive — https://policylayer.com/tools/io-github-saloprj-dialogbrain/collections-delete.md
- `files_delete` — Destructive — https://policylayer.com/tools/io-github-saloprj-dialogbrain/files-delete.md
- `folders_delete` — Destructive — https://policylayer.com/tools/io-github-saloprj-dialogbrain/folders-delete.md
- `integrations_remove_endpoints` — Destructive — https://policylayer.com/tools/io-github-saloprj-dialogbrain/integrations-remove-endpoints.md
- `messages_delete` — Destructive — https://policylayer.com/tools/io-github-saloprj-dialogbrain/messages-delete.md
- `notes_delete` — Destructive — https://policylayer.com/tools/io-github-saloprj-dialogbrain/notes-delete.md
- `reminder_cancel` — Destructive — https://policylayer.com/tools/io-github-saloprj-dialogbrain/reminder-cancel.md
- `tasks_delete` — Destructive — https://policylayer.com/tools/io-github-saloprj-dialogbrain/tasks-delete.md
- `threads_delete` — Destructive — https://policylayer.com/tools/io-github-saloprj-dialogbrain/threads-delete.md
- `widgets_delete` — Destructive — https://policylayer.com/tools/io-github-saloprj-dialogbrain/widgets-delete.md
- `youtube_delete_comment` — Destructive — https://policylayer.com/tools/io-github-saloprj-dialogbrain/youtube-delete-comment.md
- `youtube_delete_video` — Destructive — https://policylayer.com/tools/io-github-saloprj-dialogbrain/youtube-delete-video.md
- `agent_handoff` — Execute — https://policylayer.com/tools/io-github-saloprj-dialogbrain/agent-handoff.md
- `agents_simulate_inbound` — Execute — https://policylayer.com/tools/io-github-saloprj-dialogbrain/agents-simulate-inbound.md
- `android_launch_app` — Execute — https://policylayer.com/tools/io-github-saloprj-dialogbrain/android-launch-app.md
- `android_shell` — Execute — https://policylayer.com/tools/io-github-saloprj-dialogbrain/android-shell.md
- `android_ui_dump` — Execute — https://policylayer.com/tools/io-github-saloprj-dialogbrain/android-ui-dump.md
- `background_run` — Execute — https://policylayer.com/tools/io-github-saloprj-dialogbrain/background-run.md
- `browser_attach_meet` — Execute — https://policylayer.com/tools/io-github-saloprj-dialogbrain/browser-attach-meet.md
- `browser_click` — Execute — https://policylayer.com/tools/io-github-saloprj-dialogbrain/browser-click.md
- `browser_close` — Execute — https://policylayer.com/tools/io-github-saloprj-dialogbrain/browser-close.md
- `browser_drag` — Execute — https://policylayer.com/tools/io-github-saloprj-dialogbrain/browser-drag.md
- `browser_evaluate` — Execute — https://policylayer.com/tools/io-github-saloprj-dialogbrain/browser-evaluate.md
- `browser_fill` — Execute — https://policylayer.com/tools/io-github-saloprj-dialogbrain/browser-fill.md
- `browser_fill_form` — Execute — https://policylayer.com/tools/io-github-saloprj-dialogbrain/browser-fill-form.md
- …and 194 more: https://policylayer.com/tools/io-github-saloprj-dialogbrain.md

## For agents

This record is a snapshot. Live verdicts and the full registry:

- Check every server in your MCP config at once: `npx -y policylayer stack`
- Vet a server before you add it: install the mcp-precheck skill — `npx skills add https://policylayer.com` (skill text: https://policylayer.com/skill.md)
- Query the registry over MCP: endpoint `https://api.policylayer.com/mcp` — tools `check_mcp_server`, `check_mcp_stack`, `check_tool`, `search_registry`, `get_change_events`

---

Source: the PolicyLayer MCP registry — one continuously verified record per MCP server. Full record: https://policylayer.com/registry?q=io-github-saloprj-dialogbrain · API: https://policylayer.com/registry/api · Policy library: https://policylayer.com/policies/io-github-saloprj-dialogbrain