Pipecat: review, pricing, security and alternatives

What Pipecat does

Pipecat belongs to the voice agents family: agents that listen and answer out loud, on the phone or in an app, in real time. On our grid it ranks #1 of the 3 projects of this family listed in the directory.

Unlike a ready-made agent, a framework provides the parts to build one: tool calling, step sequencing, memory, coordination of several agents. It is aimed at teams that want a custom agent.

You use it from: developer SDK. Usable models: GPT (OpenAI), Gemini (Google), Claude (Anthropic), local models (Ollama, llama.cpp, vLLM…), and any OpenAI-compatible model. It can run on your own machine or server.

Who is Pipecat for?

It targets companies that want an agent able to hold a spoken conversation, on the phone or in an app. Typical tasks people give it:

• answer simple calls and book appointments
• qualify a caller before transferring
• add a voice interface to an app

It is a good candidate if your data must stay on your machines and you want the option of a local model, with no API fees.

Access and human control

A framework has no access of its own: the tools you plug in define what the agent can do. Start with read-only tools.

We could not establish whether it asks for human approval before sensitive actions: test it first on an unimportant account or folder.

Pipecat pricing

The code is free, under the BSD-2-Clause licence.

Getting started with Pipecat

1. Install it: the project ships as a Python package (install with pip or uv). The exact command is in the repository README.
2. Pick the model: an API key from a provider, or a local model if your machine has enough graphics memory (the VRAM calculator tells you).
3. Start with the minimal example from the docs, then add one tool at a time and check what the agent does with it.
4. Give it a short, checkable task, review the result and its action log, then raise the difficulty step by step.

Security: risk level

A voice agent records voices, which are sensitive personal data: inform callers and check where recordings are stored.

Three habits: least privilege (minimal rights, dedicated keys), human approval for irreversible actions, a sandbox for code execution. The AI agent security check reviews your setup in a few minutes.

Project activity and releases

Created on December 27, 2023, the pipecat-ai/pipecat repository has 16,779 stars, 2,957 forks and 118 open issues, with 14,422 commits in total. It received changes this month.

Over the last 52 weeks: 8,313 commits, an average of 159.9 per week.

124 releases in total; 30 in the last twelve months. Latest release: v1.14.0, on October 24, 2026.

Pipecat and other voice agents at a glance

The 2 best-ranked agents in the same family, 2 of them open source. The score out of 100 only applies to open-source projects; for proprietary services we show the published entry price. A dash marks information the documentation does not state.

How we rated it

Score: 82/100, computed only from public, verifiable data, with no subjective testing or partnership:

• Adoption 27/40: 16,779 stars on a log scale (40 points from about 200,000).
• Activity 30/30: last commit less than a month ago, 16 releases in six months, 8,313 commits in a year.
• Framework 25/30: licence, default human approval, self-hosting, model choice and documentation site.

The score does not say whether the agent will succeed at your tasks: it measures how solid the project is. The full grid is on the method page.