Integration

Wit.ai integration

Natural Language Processing API by Meta. Extract intents and entities from text or speech. Build chatbots, voice assistants, and conversational AI applications.

Ask it in chat

Say what should happen.
The workflow builds itself.

When this happens, do that in Wit.ai.Built from the 21 Wit.ai tools below, on the connection you add once.

Common Wit.ai use cases

  • Model review
  • Model cleanup
  • Model training
  • Entity inspection
  • App management
  • Training data management
  • Chatbot NLU
  • App overview
  • Trait overview
  • Entity overview

What you can do with Wit.ai

Each of these is one operation on one endpoint, available both as a workflow step and as a tool an AI agent can call on its own. Nothing bundles several operations into one action, so what a run did stays readable afterwards.

Most endpoints run on the free plan. A few, mainly the ones that publish on your behalf, need a paid plan.

Intent, 4 operations

  • create_intentCreate intentPOSTCreates a new intent.
  • delete_intentDelete intentDELETEDeletes an intent from the Wit.ai app.
  • get_intentGet intentGETRetrieves details for a specific intent.
  • list_intentsList intentsGETLists all intents in the Wit.ai app.

Nlp entity, 4 operations

  • delete_entityDelete entityDELETEDeletes an entity from the Wit.ai app.
  • get_entityGet entityGETRetrieves details for a specific entity.
  • list_entitiesList entitiesGETLists all entities in the Wit.ai app.
  • update_entityUpdate entityPUTUpdates entity keywords and roles.

Trait, 4 operations

  • create_traitCreate traitPOSTCreates a new trait.
  • delete_traitDelete traitDELETEDeletes a trait from the Wit.ai app.
  • get_traitGet traitGETRetrieves details for a specific trait.
  • list_traitsList traitsGETLists all traits in the Wit.ai app.

Utterance, 2 operations

  • delete_utterancesDelete utterancesDELETEDeletes training utterances from the model.
  • train_utteranceTrain utterancePOSTTrains the model with new utterances.

App, 1 operation

  • list_appsList appsGETLists all Wit.ai apps for the authenticated user.

Dictation, 1 operation

  • transcribe_dictationTranscribe dictationPOSTTranscribes audio to text without NLU extraction.

Message, 1 operation

  • get_messageGet messageGETAnalyzes text to extract intents and entities.

Speech, 1 operation

  • speech_to_textSpeech to textPOSTTranscribes speech and extracts intents.

Speech synthesis, 1 operation

  • synthesize_speechSynthesize speechPOSTGenerates speech audio from text.

Voice, 1 operation

  • list_voicesList voicesGETLists available voices for speech synthesis.

Wit entity, 1 operation

  • create_entityCreate entityPOSTCreates a new custom entity.

Use Wit.ai from Claude Code, Cursor or Codex

Connect Wit.ai in LiveContext, create an API key in Settings, then add the LiveContext MCP server to your client. Its Wit.ai operations become tools the client can call, next to every other integration you connected.

Claude Code
claude mcp add --transport http livecontext https://livecontext.ai/mcp --header "X-API-Key: YOUR_API_KEY"
Codex (~/.codex/config.toml)
[mcp_servers.livecontext]
url = "https://livecontext.ai/mcp"

[mcp_servers.livecontext.http_headers]
"X-API-Key" = "YOUR_API_KEY"
Cursor, Claude Desktop and other JSON configs
{
  "mcpServers": {
    "livecontext": {
      "type": "http",
      "url": "https://livecontext.ai/mcp",
      "headers": {
        "X-API-Key": "YOUR_API_KEY"
      }
    }
  }
}

Set up the MCP server step by step

How to connect Wit.ai

  1. Create your workspace

    Sign up free. Nothing to install.

  2. Connect Wit.ai once

    Add your Wit.ai connection in Settings. Every tool from this integration reuses it, and secrets are encrypted at rest and visible only to you.

  3. Describe the job in chat

    The workflow builds itself in front of you and picks the endpoints it needs. Drag the steps yourself on the canvas whenever you would rather be explicit.

Wit.ai integration FAQ

What can you do with the Wit.ai integration?

LiveContext exposes 21 operations on Wit.ai, covering intent, nlp entity, trait and utterance. Common uses include Model review, Model cleanup and Model training.

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