Investigate market moves and alerts with an agent on your charts

Tools

Claude, Codex

Overview

Download Desktop · Self-hosting · Features · Tea

Workflow

Download Desktop · Self-hosting · Features · Tea OpenChart brings AI agents into every step of your investment journey: statistical and technical analysis with code and charts, real-time responses to market events with alerts, opportunity discovery through agentic research, and more. OpenChart is not built to monetize software, but to explore a future where humans and agents manage assets together. If you believe in this future and want to join forces, we want to talk to you. Quick start Download Desktop for macOS (Apple Silicon), open the disk image, and install OpenChart. To run Desktop from source, install Node.js 24, npm 11.11.1, Bun 1.4.2, and Just, then run: just install also initializes and builds Tea, a programming language built for analyzing market, by the same team. Follow the setup guide for your first chart and alert, or the development guide for building and packaging the app. Desktop is free. AI usage follows your agent provider's plan; optional Cloud market data is priced separately. Key features Charts without software quotas Add indicators and Volume Profile, then expand to a 4×4 grid. No software plan limits on charts, indicators, or price and indicator alerts. Use your own agents Use your Claude, Codex, and Gemini models to research markets, build indicators, and set up alerts with the accounts you already have. Describe what to watch Tell your agent what matters. It builds Tea monitors that evaluate incoming data and investigate when a condition fires. Explain what moved the chart Select a range and let your agent research the move, with source-linked annotations pinned to the bars. Draw it, get alerted Draw a line or zone on the chart. When price crosses it, an alert can ask your agent to research the move. Write your own market logic in Tea Build custom indicators and conditions with functions, loops, state, and collections that evaluate as data flows in. Explore Tea → Staying updated Star OpenChart to support the project and help more people discover it. Credits Thank you to the projects and people whose work helps shape OpenChart: Jan: for inspiration on the app's design and visual style. TradingView's Pine Script: for inspiring Tea's language design. OpenCode: a major inspiration for OpenChart, and the project through which we discovered Effect. Dify: for inspiring the organization of this README. assistant-ui and AG-UI: for the agent conversation interface and event protocol. shadcn/ui, Radix UI, and Base UI: for reusable interface components. Effect: for the runtime, concurrency, and error-handling foundations. Inter and Hugeicons: for typography and interface icons. robust-orientation and related libraries by Mikola Lysenko, and kld-intersections by Kevin Lindsey: for geometry algorithms adapted in Tea. Thanks also to the maintainers of the many other open-source dependencies that make OpenChart possible. Contributing Help improve OpenChart through code, indicators, documentation, and feedback. Code: Start with the development guide and architecture. Run just check before submitting a pull request. Indicators: Improve OpenChart's built-in studies, or contribute to the Tea compiler and runtime. Documentation: Fix an unclear explanation, improve a setup guide, or add a useful example. Ideas and feedback: Tell us what you are building on Discord, or open an issue with a bug report or feature request. Contributors Thanks to everyone helping build OpenChart. Community & contact Discord: Ask questions, share charts and indicators, and meet other users. GitHub Issues: Report reproducible bugs and suggest improvements. X / @OpenChartHQ: Follow release news and project updates. Reddit / r/OpenChartOfficial: Share setups, discuss market research workflows, and exchange ideas. Security disclosure Report vulnerabilities privately to security@longsurf.ai, following our security policy. Please do not disclose vulnerabilities in public issues, pull requests, or community channels. License OpenChart is open source under the MIT License.

Reported result

The source does not report measured outcomes, success rates, or specific business impacts. It describes the intended workflow where agents assist in statistical analysis and opportunity discovery. To validate effectiveness, propose a measurable acceptance check: track the time saved in manual chart analysis versus agent-assisted investigation for a set number of market events.

Human role

The original post does not say how a person stayed involved.

Limitations

Prerequisites include macOS (Apple Silicon) for the desktop app or specific dev tools (Node.js 24, npm, Bun, Just) for source builds. AI usage costs depend on the user's agent provider plan, and optional Cloud market data is priced separately. The source is a project README, indicating potential feature instability or changes. Human approval is required for any financial decisions based on agent outputs.

Try it

I want to test the OpenChart agent workflow for market analysis. First, download and install OpenChart Desktop for macOS from [replaceable URL: https://github.com/longsurf-ai/openchart]. Configure it to use my [replaceable input: Claude/Codex/Gemini] account. Set up a simple Tea monitor for [replaceable input: specific asset, e.g., BTC/USD] that triggers when [replaceable input: condition, e.g., price crosses 20-day moving average]. Run a dry test on historical data for [replaceable input: date range]. Verify that the agent generates a research summary with source links. Do not execute any real trades. If the output is accurate, document the steps. If inputs are missing, ask me for the specific asset and condition before proceeding.

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