Tel-Agent

Name: Tel-Agent
Author: Dpro-at

by Dpro-at

Verified

AI phone assistant | open-source

446stars

99forks

Python

Added 9/4/2026

Installation

# Add to your Claude Code skills
git clone https://github.com/Dpro-at/Tel-Agent

Getting Started

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Security ReportVerified

Last scanned: 9/5/2026

{
  "issues": [],
  "status": "PASSED",
  "scannedAt": "2026-09-05T08:04:19.602Z",
  "npmAuditRan": true,
  "pipAuditRan": true,
  "promptInjectionRan": true
}

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README.md

Frequently Asked Questions

What is Tel-Agent?

Tel-Agent is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by Dpro-at. AI phone assistant | open-source. It has 446 GitHub stars.

Is Tel-Agent safe to use?

Yes. Tel-Agent passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install Tel-Agent?

Clone the repository with "git clone https://github.com/Dpro-at/Tel-Agent" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is Tel-Agent written in?

Tel-Agent is primarily written in Python. It is open-source under Dpro-at on GitHub, so you can review or fork the full source.

Are there alternatives to Tel-Agent?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh Tel-Agent against similar tools.

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⚠️ Third-Party Software Notice

This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.

Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.

Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.

Read the Terms of Service

AI phone assistant

Connect any phone line to any AI model. Self-hosted, bring your own keys.

tel-agent.com · maintained by Dpro GmbH, Vienna

What it is

Tel-Agent is an open-source gateway that sits between a phone line and an AI agent.

A call arrives over SIP. Tel-Agent checks the caller against your routing rules and either passes it through to a human, blocks it, or hands it to an AI agent. The agent speaks with the caller in real time, can invoke tools — transfer the call, take a message, check a calendar, call any HTTP endpoint — and every call is recorded, transcribed, and searchable.

It runs on your own hardware, on your own LAN, with your own API keys.

The same agent handles phone calls and answers on web chat, SMS, email, WhatsApp, Telegram, Messenger, Instagram, Discord and Slack — connected with your own credentials from each platform, never a shared application of ours. The official channel scope now covers 24 channels including the phone, with additional channels built on the extension contract. A channel is a route a customer uses to reach you; a system you run your own business on is an integration, and those are reached through webhooks and the HTTP tool.

What it is not

Not a PBX replacement. It connects to your existing PBX (3CX, Asterisk, FreePBX) as an extension.
Not a workflow automation platform. Webhooks and a generic HTTP tool reach n8n and Home Assistant, which do that job better. A channel is where the conversation happens; an integration is a system the agent acts on. We own the first and reach the second through the HTTP tool.
Not a CRM.
Not analog-capable. Bridge an analog line with an ATA; Tel-Agent only speaks SIP.

Why it exists

Well-funded closed products already do "AI receptionist for business". What does not exist is a good open, self-hosted one — where you own the recordings, choose the models, and decide which callers ever reach the AI at all.

Project status

Alpha. Native installers and container images are available today. Choose a platform on the download page, or get the packages from the releases page: a Windows installer, macOS packages for Apple Silicon and Intel, DEB and RPM packages for Linux, and a docker-compose.release.yml that pulls the published images. The installers are unsigned while code signing is not yet configured, so the operating system will ask once before it runs.

What works now. A conversation is answered end to end: the reply streams token by token, can be interrupted mid-sentence, is stored, and raises a notification so a person knows someone wrote in. The phone implementation includes streaming speech recognition and synthesis, interruption handling, caller-ID routing, and stored call transcripts through the SIP/LiveKit transport. Twilio integration handles SMS with customer-owned credentials. The core messaging channels are wired — web chat, WhatsApp, Telegram, Messenger, Instagram, Discord, Slack, email and SMS — and the dashboard serves them from a real API: sign-in and the account flows, home, the conversation archive, the notification tray, contacts, assistants, knowledge, the catalogue, apps, numbers, routing rules, backups, system health, settings and workspaces. The product speaks five languages: English, German, Arabic, Spanish and Dutch.

What is being added now. A second wave of channels, one issue each under the channel label: Microsoft Teams, Signal, Viber, Google Chat, Mattermost, Matrix, IRC, LINE, WeChat, WeCom, QQ, DingTalk, Feishu / Lark and iMessage. They share one declarative setup contract (#220), so each new channel is a definition plus a transport rather than a fork of the last one. More translations are open as good first issues.

Deployment. The Windows installer starts the local service and opens the dashboard in your browser. Native macOS and Linux packages and Docker images provide the other installation paths. Phone and messaging connections use your own provider credentials; configure the channels you want to use in your installation.

The full plan, and what each milestone means, is in docs/ROADMAP.md. Watch or star the repository to hear when a release lands.

Architecture

Layer	Choice
Voice agent	Python + LiveKit Agents
API	Python + FastAPI
Frontend	Next.js + React
Database	SQLite by default; PostgreSQL is also supported
Cache / queue	Redis
Reverse proxy	Caddy — automatic HTTPS
Packaging	Windows installer, macOS packages, Linux DEB/RPM and Docker Compose

Providers for v1: Deepgram (STT) · one cloud LLM · ElevenLabs (TTS). Local models (Ollama, Whisper, Piper) follow in v1.1 — they need a GPU to hold a natural conversation, so they are not the default.

Latency target: under 800 ms from the end of caller speech to the first audio out. Everything streams; the first sentence starts speaking while the rest is still being generated