pegasus-ai 0.1.7

A lightweight terminal agent framework for long-running modular agents

Pegasus

Pegasus is a terminal-first agent runtime for long-running tasks. It combines a streaming CLI, tool calling, browser control, camera capture, MCP execution, subagents, and automatic context compression in one package.

It is designed for workflows that need more than simple code generation. Pegasus can keep working across multiple turns, use tools to interact with the local machine and external systems, and continue operating even as context grows.

Pegasus treats open source models as first class citizens. It has no support for closed source models and aims to be the best agentic runtime harness for using open source models.

Features

• terminal agent workflow with streaming responses and tool execution
• built-in file, shell, edit, web search, memory, and todo tools
• browser automation with annotated screenshots for grounded actions
• camera capture with image handoff into the next model turn
• MCP executor for listing and composing MCP tools as Python-style functions
• subagents for delegated task execution
• automatic context compression when conversation history approaches the model limit
• open source models treated as first class citizens

Model Support

Pegasus currently supports the following open source models:

• kimi-k2.5
• glm5
• qwen3.5-122b
• minimax-m2.5
• olmo3.1-32b-instruct
• nemotron-3-nano-30b
• devstral2
• mercury2

Pegasus does not support closed source models.

Installation

Install from PyPI:

pip install pegasus-ai

Install from source:

git clone https://github.com/asuzukosi/pegasus.git
cd pegasus
pip install -e .

Requirements

• python 3.9 or newer
• an API key exposed as API_KEY
• optional local dependencies for advanced tools, such as a working browser environment for Playwright-based automation and a camera device for vision capture

Get an API key from OpenRouter.

Set your API key:

export API_KEY="sk-xxx"

Quick Start

Run the CLI:

pegasus-cli

Run a single prompt:

pegasus-cli --message "summarize the repository structure"

Run Pegasus from source without installing the console script:

python main.py

Basic Usage

Interactive session:

$ pegasus-cli
[user]> inspect this project and explain the main runtime flow

Single-shot invocation:

pegasus-cli --message "list the builtin tools and explain what each one is for"

Switch models from inside the CLI:

/model kimi-k2.5

List the supported models from inside the CLI:

/model list

Useful built-in commands:

• /help
• /config
• /model list
• /model <name>
• /clear
• /exit

Configuration

Pegasus loads project configuration from .pegasus/config.toml in the current working directory.

Example MCP configuration:

[mcp_servers.hackathon_manager]
enabled = true
startup_timeout_sec = 10.0
command = "node"
args = [".pegasus/mcp_servers/hackathon_manager_server.js"]
cwd = "."

[mcp_servers.event_booking]
enabled = true
startup_timeout_sec = 10.0
command = "node"
args = [".pegasus/mcp_servers/event_booking_server.js"]
cwd = "."

Examples

Ask Pegasus to inspect a codebase:

pegasus-cli --message "inspect the current project and explain how session startup works"

Use browser-based task execution:

[user]> open a browser, go to the target site, and tell me which clickable options are visible

Use camera capture in a multimodal workflow:

[user]> capture the camera feed for 10 seconds and describe what changed across the frames

Use MCP composition:

[user]> list the available mcp functions, then fetch details for the sf hackathons

Packaging

The published distribution name is pegasus-ai.

Install command:

pip install pegasus-ai

Python import package:

import pegasus