Gato

An AI sales agent harness built on Pi.

🐒 Overview

Gato turns Pi into a conversational sales representative for a messaging channel: it keeps context across sessions, personalizes each conversation from your contact data, and acts on your business systems through MCP tools. Everything that shapes the agent — its prompt, tools, and behavior — is plain files you can read and edit.

🍌 Features

• 🧠 Personalized conversations — reads your contact data and tailors each conversation to the person, passing the right identifiers to your tools while keeping them hidden from the customer.
• 💬 Memory across sessions — carries a rolling, language-aware summary of past interactions into every conversation, so returning customers are met with full context.
• 🎯 Focused context — keeps only recent conversation in view (configurable, default 60 days), so replies stay fast and on-topic even in long-running relationships.
• 🔌 Connects to your systems — exposes your business tools over MCP, so the agent can look things up and take action — orders, inventory, records — as part of the conversation.
• 🧩 Drop-in skills — add a skill (a folder of instructions) to your skills directory and the agent discovers it automatically, pulling it in whenever a conversation calls for it — no wiring or code.
• 💾 Persistent conversations — every conversation is saved automatically and can be resumed, so each customer's thread is preserved and you pick up exactly where you left off.

📦 Requirements

• Pi installed
• Credentials for your model provider (Gato defaults to the hebo provider; change it in .pi/settings.json)

🚀 Quick Start

git clone https://github.com/8monkey-ai/gato
cd gato
cp .env.template .env   # set your values, then `source .env` (or use direnv)
pi -c                   # start — continues the most recent conversation

Tip

Run pi -c from the repo so Pi picks up the project .pi/ — the system prompt, settings, extensions, and prompts that make up Gato.

🗂️ Your Content

Gato ships the agent; you provide the business context.

What	Where
Business guidelines	AGENTS.md in the repo root
Skills	.pi/skills/
Contact data	.pi/agent/user.json
Tool servers	.pi/agent/mcp.json
Sessions	~/.pi/agent/sessions/ (auto-managed by Pi)
Summary	~/.pi/agent/summary.md (auto-generated, don't edit)

mcp.json format:

{
  "mcpServers": {
    "crm": {
      "directTools": true,
      "url": "https://your-mcp-server/endpoint",
      "tools": ["check_inventory", "create_order"]
    }
  }
}

Note

Omit tools to register everything the server exposes.

⚙️ Configuration

Set via environment variables (Pi does not auto-load .env — source it or use direnv):

Variable	Default	Effect
GATO_HISTORY_DAYS	60	Days of chat history kept in context
GATO_SUMMARY_STALENESS_DAYS	3	Age before the conversation summary is regenerated

Model provider, thinking level, and other defaults live in .pi/settings.json.

🧪 Customizing

Every feature is a readable TypeScript file in .pi/extensions/, and the summary prompt is in .pi/prompts/. Edit them, add your own, or remove what you don't need — Pi auto-discovers extensions in the project .pi/.