# twilio-agent-connect

Connects third-party LLM agent runtimes to Twilio Voice, SMS, RCS, and WhatsApp. Helps set up TAC middleware for session memory, profile resolution, and multi-channel routing.

- skill · `type=skill` · Codex, ChatGPT · ★ 7604
- Author: Twilio · official OpenAI repository
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/openai/plugins/tree/HEAD/plugins/twilio-developer-kit/skills/twilio-agent-connect/SKILL.md
- Updated: 2026-10-08
- HTML: https://affpapa.org/en/nevibecode/skills/twilio-agent-connect

## What it does

This skill assists in building with Twilio Agent Connect (TAC). TAC acts as middleware between LLM tools like LangChain or OpenAI Agents SDK and Twilio communication APIs. It is not an agent runner. Instead, it routes incoming and outgoing traffic, links user profiles in Conversation Memory, and performs searches via Enterprise Knowledge.

The SDK handles voice via ConversationRelay WebSockets, along with SMS, RCS, WhatsApp, and web chat. For basic voice needs, you can run TAC in ConversationRelay-only mode. That path avoids the orchestrator setup, generating TwiML and managing voice callbacks directly.

You must provide `TWILIO_ACCOUNT_SID`, `TWILIO_AUTH_TOKEN`, `TWILIO_API_KEY`, and `TWILIO_API_SECRET` in the environment. Python builds need version 3.10 or higher. The TypeScript SDK is not published on npm yet, so you have to clone and build it manually on Node.js 22.13 or newer.

## Install

### Codex (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add openai/plugins --skill twilio-agent-connect -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/twilio-agent-connect/SKILL.md` — For all projects use ~/.agents/skills/

### Claude Code

1. **Skills CLI (Vercel)**
```bash
npx skills add openai/plugins --skill twilio-agent-connect -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/twilio-agent-connect/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/twilio-agent-connect/

### Cursor

**Manually: put the files in place**
- File: `.cursor/skills/twilio-agent-connect/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install openai/plugins twilio-agent-connect
```

2. **Manually: put the files in place**
- File: `.github/skills/twilio-agent-connect/SKILL.md`

### Gemini CLI

**Platform CLI**
```bash
gemini skills install https://github.com/openai/plugins --path plugins/twilio-developer-kit/skills/twilio-agent-connect
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/twilio-agent-connect/SKILL.md` — The legacy .windsurf/skills/ path still works

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/openai/plugins/tree/HEAD/plugins/twilio-developer-kit/skills/twilio-agent-connect/SKILL.md

## When to use it
- connect an LLM runtime to real-time voice calls via WebSocket
- persist user context and profiles across channels with Conversation Memory
- handle multi-channel message flows across SMS, WhatsApp, and RCS
- configure a ConversationRelay-only server for inbound calls

## Example prompts
- Build a Python FastAPI server using TAC and OpenAI for SMS and voice
- Set up ConversationRelay-only mode for handling incoming voice calls
- Show how to inject Twilio Conversation Memory into an OpenAI completion request

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 5c1b8623049213aa.

BEGIN THIRD-PARTY FILE 5c1b8623049213aa
````text
---
name: twilio-agent-connect
description: >
  Use when building or integrating Twilio Agent Connect (TAC) to connect
  third-party LLM agent runtimes with Twilio Voice, Messaging,
  ConversationRelay, Conversation Memory, Conversation Orchestrator, or
  Enterprise Knowledge.
---

# Twilio Agent Connect

## Overview

Twilio Agent Connect (TAC) is a Python and TypeScript SDK that integrates third-party LLM agentic applications with Twilio's communication technologies. TAC provides middleware for identity resolution, memory/context management (via Conversation Memory), conversation orchestration (via Conversation Orchestrator), and multi-channel handling (Voice, SMS, RCS, WhatsApp, Chat).

**Key Architecture Principle**: TAC is not an agent runtime itself—it's middleware that enables existing LLM applications (OpenAI Agents SDK, Bedrock, LangChain, Microsoft Foundry, etc.) to leverage Twilio Conversations services.

## Product Context

### Core Twilio Conversations Services

TAC integrates with three core Twilio Conversations services:

1. **Conversation Memory (Memory Store)** - Persistent user context and memory management
   - Profile storage with traits and attributes
   - Observation and summary storage
   - Session history with full conversation context
   - Identity resolution (profile lookup by phone/email)

2. **Conversation Orchestrator** - Multi-channel conversation lifecycle management
   - Unified conversation API across all channels
   - Participant management
   - Communication routing
   - Conversation grouping and configuration

3. **Enterprise Knowledge** - Knowledge base integration
   - Semantic search across knowledge bases
   - RAG (Retrieval-Augmented Generation) support
   - Knowledge chunk retrieval with relevance scoring

### Supported Channels

TAC provides built-in support for:
- **Voice** - ConversationRelay (WebSocket-based real-time voice)
- **SMS** - Text messaging
- **RCS** - Rich Communication Services
- **WhatsApp** - WhatsApp Business messaging
- **Chat** - Web chat integrations

All channels support both inbound (customer-initiated) and outbound (agent-initiated) conversations.

### ConversationRelay-Only Mode

TAC supports a simplified "ConversationRelay-only" mode for getting started with voice conversations without requiring Conversation Orchestrator or Conversation Memory setup. This mode provides:
- TwiML generation
- WebSocket protocol handling
- Voice conversation lifecycle management
- Callback-based message processing

## Installation

### Python SDK

**Requirements**: Python 3.10+

```bash
# Using uv (recommended)
uv add git+https://github.com/twilio/twilio-agent-connect-python.git

# With server support (includes FastAPI and uvicorn for TACFastAPIServer)
uv add git+https://github.com/twilio/twilio-agent-connect-python.git --extra server

# Using pip
pip install git+https://github.com/twilio/twilio-agent-connect-python.git
pip install "git+https://github.com/twilio/twilio-agent-connect-python.git[server]"
```

### TypeScript SDK

**Requirements**: Node.js 22.13+

```bash
````
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First 3073 of 16835 bytes. © Twilio · MIT · https://github.com/openai/plugins/tree/HEAD/plugins/twilio-developer-kit/skills/twilio-agent-connect/SKILL.md

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