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tau

A Python port of Pi’s minimalist coding agent.

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README

From the repo.

Tau — a Python coding-agent harness inspired by Pi

A small, readable terminal coding agent — and a working example of how coding agents are built.

Documentation · Quickstart · Architecture · PyPI · Roadmap

Join the Tau Discord community →


What is Tau?

Tau is a coding agent that lives in your terminal. You type requests like "explain this repo", "add tests", or "fix this stack trace"; Tau can read files, edit code, run commands, and keep a durable session history while streaming what it is doing.

Tau is also meant to be read. It is a teaching project for understanding the shape of a coding-agent system without starting from a giant production codebase.

tau_coding  →  tau_agent  →  tau_ai
  • tau_ai translates model providers into Tau's provider-neutral stream.
  • tau_agent owns the portable brain: messages, tools, events, loop, harness, and session primitives.
  • tau_coding wraps the brain as a real coding app: CLI, TUI, file/shell tools, provider config, project instructions, skills, and on-disk sessions.

The important boundary is:

AgentHarness = reusable brain
CodingSession = coding-agent environment
TUI = one possible frontend

The core does not know about Textual, Rich, local config paths, slash commands, or rendering. Frontends consume events.

Install

Tau is published on PyPI as tau-ai and installs a tau command. It requires Python 3.12 or newer. The recommended installers use uv and install it first when necessary.

macOS and Linux:

curl -LsSf https://twotimespi.dev/install.sh | sh

Windows PowerShell:

irm https://twotimespi.dev/install.ps1 | iex

The installers do not use sudo. They announce before installing uv, install Tau in an isolated tool environment, verify tau --version, and report if a shell restart is needed. You can inspect the shell installer or PowerShell installer before running it.

Already have a package manager? Install Tau directly:

uv tool install tau-ai
# or
pipx install tau-ai
# or
python -m pip install tau-ai

Then check it worked:

tau --version

Tau is also available on conda-forge, and can be installed using pixi:

pixi global install tau-ai

Upgrade a normal installation with:

tau update

For local development:

git clone https://github.com/huggingface/tau.git
cd tau
uv sync --dev
uv run tau --version

To make the checkout-backed command available globally, install it as an editable tool:

uv tool install --editable --force .

Run that command again after git pull. Editable installs expose source-code changes immediately, but the tool environment's package metadata, dependencies, and entry points are only refreshed when uv reinstalls the tool. Without the refresh, tau --version can still show the version from the previous install.

Quickstart

Run Tau from the project you want it to work on:

cd my-project
tau

Then type a request and press Enter:

explain what this project does

One-shot print mode is useful for scripts and quick prompts:

tau -p "summarize the architecture"
tau --cwd /path/to/project -p "find the CLI entry point"

Tau needs a model provider. Start Tau and connect one with /login:

tau
/login
/login openai
/login openai-codex
/model

Tau ships with support for OpenAI, Anthropic, OpenAI Codex subscription auth, OpenRouter, Hugging Face, and custom OpenAI-compatible endpoints, including local models. See the providers guide.

The built-in catalog lives in src/tau_coding/data/catalog.toml; add your own providers and models by dropping a ~/.tau/catalog.toml with the same schema — no code changes required.

What Tau can do

  • Interactive Textual TUI and non-interactive print mode.
  • Built-in coding tools: read, write, edit, and bash.
  • Durable JSONL sessions under ~/.tau/sessions/ with resume and branching.
  • Slash commands for login, model selection, sessions, compaction, export, theme, and more.
  • Project instructions from AGENTS.md, .tau/, and .agents/ resources.
  • User skills, prompt templates, and custom TUI themes.
  • Context accounting, manual compaction, and optional automatic compaction.
  • Provider-neutral event rendering for Rich, plain text, JSON, transcripts, and custom frontends.

Philosophy

Tau follows a few rules:

  • Small layers beat magic. Each package has one job and can be read alone.
  • Events are the contract. Providers, renderers, the TUI, and custom frontends meet at a typed event stream.
  • The core stays portable. The reusable harness does not depend on the CLI, Textual, Rich, or Tau's file layout.
  • Tools are ordinary typed functions. A tool is a schema plus an async executor returning a structured result.
  • Sessions are durable and inspectable. History is append-only JSONL; active context can be compacted without rewriting the record.
  • Documentation follows implementation. The public docs explain the result; dev-notes/ preserves the phase-by-phase build journal.

Use Tau as a library

from tau_agent import AgentHarness, AgentHarnessConfig

harness = AgentHarness(
    AgentHarnessConfig(
        provider=provider,
        model="my-model",
        system="You are a helpful coding agent.",
        tools=tools,
    )
)

async for event in harness.prompt("Explain this package"):
    print(event)

Because the harness emits events instead of rendering UI directly, the same core can drive the built-in TUI, print mode, or a frontend you build yourself.

Development

See CONTRIBUTING.md for project philosophy, layer boundaries, testing expectations, and pull request guidelines.

uv sync --dev
uv run pytest
uv run ruff check .
uv run ruff format --check .
uv run mypy

Run Tau from the checkout:

uv run tau
uv run tau -p "explain this repo"

Run the Hugo documentation site:

cd website
hugo server -D

Open http://localhost:1313/. Build with hugo --minify.

Documentation

User docs are published at https://twotimespi.dev/ and live in website/content/.

Useful entry points:

Tau is under active development. The implementation roadmap is tracked in GitHub issue #1.

License

Tau is released under the MIT License.

Collected info

  • ★ 2,854 stars
  • ⎇ 358 forks
  • Language: Python
  • Source updated: 9/25/2026

Config for your environment

Replace {MCP_ENDPOINT_URL} with this MCP’s endpoint URL (from its repo or docs above). No API key — you connect directly.

Tool

OS

Config file: ~/.cursor/mcp.json

{
  "mcpServers": {
    "mcp-server": {
      "url": "{MCP_ENDPOINT_URL}"
    }
  }
}

Paste into mcpServers in the config file. Restart Cursor after saving.

If this MCP is also published on mcpchannel.ai, you can subscribe from Browse and use the gateway config there instead.