OpenAlgo CLI

OpenAlgo CLI - a command-line client for the OpenAlgo API, built for AI agents, scripts, and automation

OpenAlgo CLI is a single Go binary that talks to your own OpenAlgo server over its REST and WebSocket APIs. It places and manages orders, reads positions, funds and holdings, pulls quotes, depth and historical candles, works with option chains and Greeks, operates Strategy Module runs, and streams live market data, with any broker OpenAlgo supports.

The CLI never connects to a broker directly. It sends requests to your OpenAlgo server, and the server's API key resolves the broker session.

The CLI is open source under the Apache-2.0 license: github.com/marketcalls/openalgo-cli.

For a step-by-step walkthrough with screenshots, read the tutorial OpenAlgo CLI: Trade, Stream and Automate Your Broker from the Terminal.

The CLI is an alpha preview. Commands, flags, and output formats may change between releases. The installed binary is the source of truth: run openalgo --help-all to see what your version supports.

Built for Agents

The CLI is designed for AI agents, scripts, and automation pipelines first:

• Every parameter is an explicit --flag. Flag names are the API field names in kebab-case (trigger_price becomes --trigger-price).

• Every API command returns the OpenAlgo JSON response on stdout.

• Errors are JSON on stderr with meaningful exit codes.

• --help-all and --schema let an agent discover commands and response shapes at runtime without calling the API.

• --dry-run previews any state-changing request without sending it.

It is not an interactive trading terminal. There are no confirmation prompts, and every command executes immediately against whatever your OpenAlgo server is connected to. Whether an order is simulated or live depends on the server's analyzer mode (sandbox mode), not on the CLI.

Use Cases

Use case	How the CLI helps
AI agent harnesses	Give Claude Code, Codex, the Claude Agent SDK, or any tool-calling harness a shell tool and the CLI. The agent reads positions, funds and quotes, reasons about them, and places or manages orders. See AI Agents.
Human-in-the-loop execution	An agent or script proposes an order with --dry-run, a human or policy layer approves the exact request body, and the same command is sent without --dry-run.
Scheduled automation	Cron jobs, CI, or task schedulers square off positions, snapshot P&L, or alert on rejected orders with a few lines of shell.
Multiple brokers and instances	One profile per OpenAlgo instance (-p zerodha, -p dhan) lets a single script or agent report on or act across every account.
Research and data pipelines	Historical candles, the instrument master, option chains, and Greeks go straight into pandas, DuckDB, or spreadsheets with --csv.
Live monitoring	openalgo stream ltp, quote, depth, and orders emit NDJSON for alerting scripts, dashboards, or an agent watching order updates.
Strategy Module operations	Start, stop, and audit strategies (runs, orders, risk events) from scripts or chat-ops.
Ops and debugging	openalgo doctor checks connectivity, the broker session, and analyzer mode. --debug and --trace show the exact request with the API key redacted, which helps reproduce a TradingView or Amibroker integration issue.
Universal adapter	Anything that can run a process (Excel VBA, Node, Rust, n8n, Make) can drive OpenAlgo without an SDK.

When Not to Use It

• Latency-sensitive, tick-by-tick strategies. Each command starts a new process and makes a fresh HTTP request. Use the Python SDK or the WebSocket API directly.

• Long conversational sessions. When an assistant is exploring an account interactively over many turns, the MCP server fits better.

CLI Compared to MCP

Both let an AI agent work with a running OpenAlgo instance.

	OpenAlgo CLI	MCP
Interface	Shell commands with flags	Tool calls over the Model Context Protocol
Runs as	A single binary, one process per command	A long-running MCP server process
Works with	Any agent or script that can run a shell command, plus cron, CI, and other languages	MCP clients such as Claude Desktop, Cursor, and Windsurf
Output	JSON by default, CSV with --csv, filtered with --jq	Tool results returned to the model
Previewing writes	--dry-run prints the exact request body	Depends on the client's approval flow
Live data	stream commands emit NDJSON over WebSocket	Request and response only
Multiple instances	Profiles, selected per command with -p	One server entry per instance
Good for	Automation, scheduled jobs, pipelines, and agents with a shell tool	Conversational exploration of the account

They compose. An agent can use MCP for conversation and the CLI for scripted, repeatable, or scheduled work.

Quick Start

1. Install the CLI. See Installation.

curl -fsSL https://raw.githubusercontent.com/marketcalls/openalgo-cli/main/install.sh | sh

1. Save the server address and API key in a profile. See Authentication and Profiles.

openalgo profile login

1. Check connectivity and the trading mode.

openalgo ping
openalgo analyzer status

1. Read the account and market data.

openalgo account funds
openalgo position list
openalgo data quote --symbol RELIANCE --exchange NSE
openalgo data history --symbol SBIN --exchange NSE --interval 5m --start-date 2026-09-01 --end-date 2026-09-25

1. Preview an order, then place it.

openalgo order place --symbol SBIN --exchange NSE --action BUY --quantity 1 --pricetype LIMIT --price 800 --product CNC --dry-run
openalgo order place --symbol SBIN --exchange NSE --action BUY --quantity 1 --pricetype LIMIT --price 800 --product CNC
openalgo order list

Safety

Destructive commands act immediately and without confirmation:

• openalgo position close-all squares off every open position in the account. --strategy is a tag, not a filter.

• openalgo order cancel-all cancels every open order in the account.

• openalgo strategy close-all exits every open leg of a strategy run.

• openalgo analyzer toggle --mode=false switches the server out of analyzer mode, so every later order goes to the broker as a live order.

Run openalgo analyzer status before placing orders when you are not sure which mode the server is in. See Responsibilities.

Pages in This Section

Page	Covers
Installation	Install scripts, Go, source builds, verification, and updates
Authentication and Profiles	Profiles, environment variables, and multiple OpenAlgo instances
Command Reference	Every command, its API endpoint, and an example
Output, Errors and Automation	JSON, CSV, jq, schemas, dry runs, errors, exit codes, and retries
Streaming	Live LTP, quote, depth, and order updates over WebSocket
AI Agents	Using the CLI and its agent skill inside agent harnesses