AI Skill Hub 强烈推荐:Patter 是一款优质的MCP工具。AI 综合评分 8.0 分,在同类工具中表现稳健。如果你正在寻找可靠的MCP工具解决方案,这是一个值得深入了解的选择。
Patter 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
Patter 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/PatterAI/Patter
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"patter": {
"command": "npx",
"args": ["-y", "patter"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 Patter 执行以下任务... Claude: [自动调用 Patter MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"patter": {
"command": "npx",
"args": ["-y", "patter"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
<p align="center"> <picture> <source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/PatterAI/Patter/main/docs/github-banner.png" /> <source media="(prefers-color-scheme: light)" srcset="https://raw.githubusercontent.com/PatterAI/Patter/main/docs/github-banner.png" /> <img src="https://raw.githubusercontent.com/PatterAI/Patter/main/docs/github-banner.png" alt="Patter SDK" width="100%" /> </picture> </p>
<p align="center"> <a href="https://pypi.org/project/getpatter/"><img src="https://img.shields.io/pypi/v/getpatter?logo=pypi&logoColor=white&label=pip%20install%20getpatter" alt="PyPI" /></a> <a href="https://www.npmjs.com/package/getpatter"><img src="https://img.shields.io/npm/v/getpatter?logo=npm&logoColor=white&label=npm%20install%20getpatter" alt="npm" /></a> <a href="./LICENSE"><img src="https://img.shields.io/badge/license-MIT-green" alt="MIT License" /></a> <img src="https://img.shields.io/badge/python-3.11%2B-blue?logo=python&logoColor=white" alt="Python 3.11+" /> <img src="https://img.shields.io/badge/typescript-5.0%2B-3178c6?logo=typescript&logoColor=white" alt="TypeScript 5+" /> </p>
<p align="center"> <a href="#quickstart">Quickstart</a> • <a href="#features">Features</a> • <a href="#templates">Templates</a> • <a href="#configuration">Configuration</a> • <a href="https://docs.getpatter.com">Docs</a> </p>
---
Patter is the open-source SDK that gives your AI agent a phone number. Point it at any function that returns a string, and Patter handles the rest: telephony, speech-to-text, text-to-speech, and real-time audio streaming. You build the agent — we connect it to the phone.
| Feature | Method | Template |
|---|---|---|
| Inbound calls | phone.serve(agent) | [patter-inbound-agent](https://github.com/PatterAI/patter-inbound-agent) |
| Outbound calls + AMD | phone.call(to, machineDetection) | [patter-outbound-calls](https://github.com/PatterAI/patter-outbound-calls) |
| Tool calling (webhooks) | agent(tools=[...]) | [patter-tool-calling](https://github.com/PatterAI/patter-tool-calling) |
| Custom STT + TTS | agent(provider="pipeline") | [patter-custom-voice](https://github.com/PatterAI/patter-custom-voice) |
| Dynamic variables | agent(variables={...}) | [patter-dynamic-variables](https://github.com/PatterAI/patter-dynamic-variables) |
| Custom LLM (any model) | serve(onMessage=handler) | [patter-custom-llm](https://github.com/PatterAI/patter-custom-llm) |
| Dashboard + metrics | serve(dashboard=True) | [patter-dashboard](https://github.com/PatterAI/patter-dashboard) |
| Output guardrails | agent(guardrails=[...]) | [docs](https://docs.getpatter.com) |
| Call recording | serve(recording=True) | [docs](https://docs.getpatter.com) |
| Call transfer | transfer_call (auto-injected) | [docs](https://docs.getpatter.com) |
| Voicemail drop | call(voicemailMessage="...") | [patter-outbound-calls](https://github.com/PatterAI/patter-outbound-calls) |
| Test mode (no phone) | phone.test(agent) | [docs](https://docs.getpatter.com) |
| Built-in tunnel | Cloudflare (auto) | [docs](https://docs.getpatter.com) |
| Phone-as-a-tool (LangChain / OpenAI Assistants / Hermes) | PatterTool(phone, agent).execute(...) | [docs](https://docs.getpatter.com) |
docker compose up
See Dockerfile and docker-compose.yml for the default configuration.
Set the env vars your carrier and engine need:
Twilio
export TWILIO_ACCOUNT_SID=ACxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
export TWILIO_AUTH_TOKEN=your_auth_token
export OPENAI_API_KEY=sk-xxxxxxxxxxxxxxxxxxxxxxxx
Telnyx
export TELNYX_API_KEY=KEYxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
export TELNYX_CONNECTION_ID=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export OPENAI_API_KEY=sk-xxxxxxxxxxxxxxxxxxxxxxxx
<details open> <summary><strong>Python</strong></summary>
pip install getpatter
from getpatter import Patter, Twilio, OpenAIRealtime
phone = Patter(carrier=Twilio(), phone_number="+15550001234")
agent = phone.agent(engine=OpenAIRealtime(), system_prompt="You are a friendly receptionist for Acme Corp.", first_message="Hello! How can I help?")
await phone.serve(agent, tunnel=True)
Or with Telnyx:
from getpatter import Patter, Telnyx, OpenAIRealtime
phone = Patter(carrier=Telnyx(), phone_number="+15550001234")
agent = phone.agent(engine=OpenAIRealtime(), system_prompt="You are a friendly receptionist for Acme Corp.", first_message="Hello! How can I help?")
await phone.serve(agent, tunnel=True)
</details>
<details> <summary><strong>TypeScript</strong></summary>
npm install getpatter
import { Patter, Twilio, OpenAIRealtime } from "getpatter";
const phone = new Patter({ carrier: new Twilio(), phoneNumber: "+15550001234" });
const agent = phone.agent({ engine: new OpenAIRealtime(), systemPrompt: "You are a friendly receptionist for Acme Corp.", firstMessage: "Hello! How can I help?" });
await phone.serve({ agent, tunnel: true });
Or with Telnyx:
import { Patter, Telnyx, OpenAIRealtime } from "getpatter";
const phone = new Patter({ carrier: new Telnyx(), phoneNumber: "+15550001234" });
const agent = phone.agent({ engine: new OpenAIRealtime(), systemPrompt: "You are a friendly receptionist for Acme Corp.", firstMessage: "Hello! How can I help?" });
await phone.serve({ agent, tunnel: true });
</details>
tunnel: true spawns a Cloudflare quick tunnel and points your Twilio number at it — great for dev / acceptance. For production outbound calls (especially on Twilio), replace it with ngrok or a static webhook_url to avoid WSS upgrade races on first call. See Tunneling for details.
Every carrier and provider reads its credentials from environment variables by default; see each SDK's README for the full catalog.
git clone https://github.com/PatterAI/patter-inbound-agent cd patter-inbound-agent cp .env.example .env # fill in your keys cd python && pip install -r requirements.txt && python main.py ```
| Variable | Required | Description |
|---|---|---|
OPENAI_API_KEY | Yes (Realtime mode) | OpenAI API key with Realtime access |
TWILIO_ACCOUNT_SID | Yes | Twilio account SID |
TWILIO_AUTH_TOKEN | Yes | Twilio auth token |
TWILIO_PHONE_NUMBER | Yes | Your Twilio phone number (E.164) |
TELNYX_API_KEY | Yes (Telnyx) | Telnyx API key |
TELNYX_CONNECTION_ID | Yes (Telnyx) | Telnyx Call Control Application connection ID |
TELNYX_PHONE_NUMBER | Yes (Telnyx) | Your Telnyx phone number (E.164) |
DEEPGRAM_API_KEY | Pipeline mode | Deepgram STT key |
ELEVENLABS_API_KEY | Pipeline mode | ElevenLabs TTS key |
ANTHROPIC_API_KEY | Custom LLM | For bringing your own model |
WEBHOOK_URL | No | Public URL (auto-tunneled via Cloudflare if omitted) |
```bash cp .env.example .env
```
Telnyx: Telnyx is a fully supported telephony provider alternative to Twilio. Both carriers receive equal support for DTMF, transfer, and metrics. Recording parity is supported via Telnyx Call Control; consult the Telnyx portal for configuration details.
cd libraries/python && pip install -e ".[dev]" && pytest tests/ -v
cd libraries/typescript && npm install && npm test ```
Please open an issue before submitting large changes so we can discuss the approach first.
Patter is purpose-built for production voice over real telephony. Out of the box you get Twilio + Telnyx parity (DTMF, transfer, AMD, voicemail drop, recording), both architectures from one API — speech-to-speech (Realtime / ConvAI engines) and the sandwich pipeline (STT → LLM → TTS) — and production-grade barge-in / VAD / IVR primitives that work the same on every carrier. Observability is vendor-neutral OpenTelemetry tracing, plus a built-in dashboard and tunnel; no extra collector required. The 4-line quickstart above replaces ~50 lines of glue you'd otherwise write against a generic voice-agent toolkit, and the Python and TypeScript SDKs are identical — same surface, same hooks, same events — so cross-runtime teams ship the same agent twice without rewriting it.
高质量的开源MCP工具,支持语音AI功能
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
总体来看,Patter 是一款质量优秀的MCP工具,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | Patter |
| 原始描述 | 开源MCP工具:Open-source voice-AI SDK. The Vapi/Retell alternative for builders who want to o。⭐99 · Python |
| Topics | ai-agentconversational-aillm |
| GitHub | https://github.com/PatterAI/Patter |
| License | MIT |
| 语言 | Python |
收录时间:2026-05-25 · 更新时间:2026-05-26 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端