saarthi-cli 0.1.2

Your AI copilot in the terminal - a LangGraph-powered CLI chatbot with long-term memory

Saarthi CLI

Saarthi (सारथी) means guide or companion in Hindi.

Your AI copilot in the terminal.

Saarthi is a LangGraph-powered CLI chatbot with persistent memory, real-time token streaming, MCP integration, and multi-provider LLM support. It runs entirely inside the terminal with a custom TUI built using prompt-toolkit.

No browser. No Electron. No cloud dashboard.

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Demo

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Features

• Short-term and long-term memory support
• Local SQLite-backed conversation persistence
• Named chat sessions with resume support
• Real-time token streaming
• Live tool-call visualisation
• MCP (Model Context Protocol) server support
• Interactive terminal UI built with prompt-toolkit
• Multi-provider LLM support
• Local-first architecture — no data leaves your machine
• Built-in developer tools

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Supported providers

• OpenAI
• Google Gemini
• Mistral AI

More providers (including Anthropic and local model support) are planned.

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Built-in tools

Tool	Description
bash	Execute shell commands and Python snippets
calculator	Evaluate mathematical expressions
ddg_tool	DuckDuckGo web search
wiki_tool	Wikipedia lookup
arxiv_tool	arXiv paper search

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Installation

Using pip

pip install saarthi-cli
saarthi

Using uv

uv tool install saarthi-cli
saarthi

From source

git clone https://github.com/snehangshu2002/saarthi-cli.git
cd saarthi-cli
uv sync
uv run python main.py

Linux / macOS install script

curl -fsSL https://raw.githubusercontent.com/snehangshu2002/saarthi-cli/main/install.sh | bash

Note: The install script is for Linux and macOS only. Windows users should install via pip install saarthi-cli or uv tool install saarthi-cli.

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First-time setup

On first launch, Saarthi walks you through a one-time setup:

1. Choose a username
2. Select an LLM provider
3. Enter your API key (input is hidden)

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Local storage

All configuration and memory are stored locally — nothing is sent to any external service beyond your chosen LLM provider.

Platform	Storage Path
Windows	%LOCALAPPDATA%\saarthi\
Linux / macOS	~/.local/share/saarthi/

Contents:

• settings.json — provider and user config
• mcp_config.json — MCP server definitions
• SQLite database — conversation memory

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Commands

Command	Description
/help	Show available commands
/new	Start a new session
/resume	Resume an older session
/settings	View current configuration
/mcp	Show connected MCP servers
/exit	Quit Saarthi

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MCP support

Saarthi supports MCP-compatible servers over STDIO transport. Edit mcp_config.json in your local storage directory to add servers.

Default configuration:

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-filesystem",
        "/path/to/dir"
      ],
      "transport": "stdio"
    }
  }
}

You can connect MCP servers for filesystem access, browser automation, databases, coding agents, external APIs, and custom tools.

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Memory system

Saarthi supports two memory layers:

• Short-term memory — active conversation context
• Long-term memory — persisted locally in SQLite across sessions

Conversation history can also be summarised automatically to reduce context size while preserving important information.

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Roadmap

• Human-in-the-loop workflows
• Planning mode
• Autonomous execution mode
• Skill system support
• Export conversations
• Anthropic and local model support
• Plugin-style custom tools
• Better configuration management
• More CLI-agent style workflows

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Project structure

src/chatbot_cli/
├── app.py
├── chatbot.py
├── ui.py
├── streaming.py
├── tool.py
├── memory.py
├── sessions.py
├── providers.py
├── mcp_client.py
├── settings.py
└── clipboard.py

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License

MIT — see LICENSE for details.