TradingAgents

Vibe-Trading is an open-source AI personal trading agent and quantitative-finance research workspace developed by HKUDS. It turns natural-language finance questions into runnable analysis and backtesting workflows by connecting an agent to market-data loaders, portfolio and backtesting engines, report generation, persistent memory, and multi-agent research teams across asset classes. Its quantitative and risk-analysis capabilities include strategy backtesting, Heston stochastic-volatility pricing, hierarchical risk parity, copulas, and market-microstructure estimators. The project provides API and MCP interfaces, broker and market-data connectors, portfolio-management and broker-authorized trading workflows, examples, documentation, a demo, and a Shadow Account for testing. It supports read-only account sources such as official IBKR MCP and opt-in Binance USD-M snapshots, while scheduling actions require explicit confirmation and live-order safeguards fail closed on contradictory or invalid data. Implemented as a Python project, it uses a connector onboarding system that stores connection secrets in the operating-system keyring and is distributed under an open-source license.

AgentOps is an open-source observability and developer-tools platform for building, evaluating, and monitoring AI agents. Its Python SDK records agent sessions and LLM calls for dashboard-based session replays, step-by-step execution graphs, debugging, analytics, cost tracking, and benchmarking. Developers instrument code with decorators for sessions, agents, operations, tasks, and workflows; these support nested span hierarchies, input and output recording, exception handling, asynchronous functions, generators, and custom attributes. The SDK provides integrations with agent frameworks and LLM systems including CrewAI, AG2/AutoGen, Agno, LangGraph, and the OpenAI Agents SDK, and the platform can be self-hosted with its dashboard and API backend. The app is released under the MIT license.

FrontierAgent is an open-source agent runtime, terminal product, and evaluation suite for long-horizon research and file-based work. Its native terminal TUI provides a ReAct workflow in which one stateful agent researches, reads files, writes deliverables, runs commands, and iterates in a task-scoped sandbox, and an Agent Team workflow in which a coordinator maintains a task board, delegates bounded independent assignments to parallel sub-agents, collects structured reports, and synthesizes the result. Shell and file tools use a shared sandbox with read-only /inputs, working-state /workspace, and persistent /outputs directories. The TUI supports queued instructions during execution, approval-required diffs for mutating operations, local action traces, checkpointed sessions, resumption, and reversion. The same workflow engine powers a subprocess benchmark runner with deterministic artifact collection, concurrency, progress inspection, and reruns of individual failures. The repository also documents connection to the OpenAI-compatible Apodex-1.1 endpoint through the Apodex API.

useAgent is an open-source AI coworker that gives Claude Code, Codex, OpenCode, and Pi a shared workspace with isolated Linux computers, repositories, terminals, browsers, and team tools. It can handle research, websites, spreadsheets, reports, presentations, and code changes, returning usable files, artifacts, or pull requests through a web app, Slack, REST API, or scheduled tasks. Each run is stored as an event log in Postgres and uses a common event contract across supported agent engines. Daytona or CubeSandbox provides the isolated workstation, while integrations cross a trusted gateway as typed tools so credentials remain on the control plane rather than entering the sandbox. The workspace also supports versioned skills and playbooks, team knowledge and memory, approval-gated tools, revisioned workpieces, and durable sessions. The repository describes useAgent as alpha software with changing APIs and schemas. It can be self-hosted on Linux using Bun and Postgres with pgvector, and is licensed under AGPL-3.0-only; a commercial license is available for proprietary embedding, distribution, OEM, or white-label use.

NautilusTrader is an open-source, Rust-native engine and platform for multi-asset, multi-venue algorithmic trading. Its deterministic, event-driven architecture spans research, simulation, backtesting, and live execution, using Python as the control plane for strategy logic, configuration, and orchestration while also supporting systems written entirely in Rust. The same execution semantics and deterministic time model are used in research and live systems, allowing strategies to move from research to production without code changes. Modular adapters connect venues through REST APIs or WebSocket feeds; the engine supports historical quote, trade, bar, order-book, and custom data, multi-venue strategies, advanced order types, optional Redis-backed state persistence, and training AI trading agents with reinforcement-learning or evolutionary-strategy methods. It runs on Linux, macOS, and Windows and can be deployed with Docker.