QuantDinger

QuantDinger Open-source AI Trading OS Turn trading ideas into Python strategies, backtests, paper trading, live execution, and monitoring — all in one self-hosted stack. QuantDinger is a product of Open Byte Inc. AI research → Strategy code → Backtest → Paper/Live execution → Monitoring

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> QuantDinger can submit real orders when live trading is explicitly enabled. > Start with paper trading, use restricted API keys, and review the risk and > compliance requirements for your jurisdiction. This project does not provide > investment advice.

What QuantDinger is

QuantDinger is an open-source AI Trading OS for independent traders, Python strategy authors, and small teams. Its local-first, self-hosted design keeps market data, strategy code, broker credentials, and deployment under the operator's control.

The project combines:

• multi-provider AI market research and analysis;
• Python indicators and Strategy API V2 development;
• server-side backtesting and experiment workflows;
• paper and live execution across crypto exchanges and traditional brokers;
• web, mobile H5, human API, Agent Gateway, and MCP access;
• PostgreSQL-backed state, durable workers, audit logs, and optional monitoring.

It is not a black-box signal service. Strategy code, risk settings, credentials, and deployment remain under the operator's control.

What changed in v5

The v5 backend is organized around explicit runtime and operational boundaries:

• the HTTP API no longer owns long-running trading or scheduler loops;
• trading, scheduling, Celery jobs, and migrations run as separate processes;
• Celery handles finite, retryable work while long-lived strategy runtimes stay

in the trading worker;

• cache Redis and durable job Redis use separate instances and eviction policies;
• high-risk API contracts are represented in OpenAPI and protected by tests;
• JSON logs, request IDs, Prometheus metrics, dashboards, and alert rules are

available through an optional observability overlay;

• the production overlay runs backend processes as a non-root user with a

read-only root filesystem, dropped capabilities, and resource limits;

• CI checks syntax, lint, tests, release gates, Compose files, dependencies,

source security, secrets, API compatibility, version drift, and text encoding.

The source version is declared in [VERSION](VERSION). Git release tags use the same semantic version with a leading v, for example v5.0.1.

Architecture

The editable source is available as architecture-v5.svg.

The diagram above shows the complete product and process architecture. The runtime topology below focuses on container-to-container ownership and data flow.

flowchart TB
    C["Web / Mobile / API / MCP clients"]
    FE["Nginx frontend services"]
    API["Flask + Gunicorn API"]
    PG[("PostgreSQL")]
    CACHE[("Redis cache")]
    JOBS[("Redis jobs")]
    TW["Trading worker"]
    SW["Scheduler worker"]
    CW["Celery worker"]
    BEAT["Celery beat"]
    PROM["Prometheus"]
    GRAF["Grafana"]
    ALERT["Alertmanager"]

    C --> FE --> API
    API --> PG
    API --> CACHE
    API -->|"durable commands"| PG
    TW -->|"leases, orders, heartbeats"| PG
    SW -->|"schedules, monitoring, heartbeats"| PG
    API -->|"finite async jobs"| JOBS
    BEAT --> JOBS --> CW
    CW --> PG
    API -. metrics .-> PROM
    PG -. exporter .-> PROM
    CACHE -. exporter .-> PROM
    JOBS -. exporter .-> PROM
    PROM --> GRAF
    PROM --> ALERT

One backend image is reused by several containers with different commands:

| Process | Responsibility | | --- | --- | | migration | Applies the database schema and exits before application services start. | | backend | Handles HTTP, authentication, validation, and durable command submission. | | trading-worker | Owns strategy runtimes, pending orders, broker sessions, and reconciliation. | | scheduler-worker | Runs portfolio, deployment, payment, and signal schedules. | | celery-worker | Executes finite AI, backtest, experiment, report, and maintenance jobs. | | celery-beat | Dispatches periodic Celery tasks. |

See [Backend process roles](docs/architecture/PROCESSROLESANDTASKS.md), [architecture](docs/architecture/ARCHITECTURE.md), and [concurrency model](docs/architecture/CONCURRENCYMODEL.md) for the ownership rules.

Quick start

Option A: prebuilt images

Prerequisites: Docker with Compose v2. Node.js and a local Python environment are not required.

Linux or macOS:

curl -fsSL https://raw.githubusercontent.com/OpenByteInc/QuantDinger/main/install.sh | bash

Windows PowerShell:

irm https://raw.githubusercontent.com/OpenByteInc/QuantDinger/main/install.ps1 | iex

The installer asks for the initial administrator credentials, generates the required secrets, downloads the GHCR Compose stack, and starts it.

Open:

• Web:
• Mobile H5:
• API health:

Docker administrator and settings notes

Detailed guides: [English](docs/deployment/ADMINANDSETTINGSTROUBLESHOOTINGEN.md) | [中文](docs/deployment/ADMINANDSETTINGSTROUBLESHOOTINGCN.md)

On a fresh database, the backend creates the initial administrator from ADMIN_USER, ADMIN_PASSWORD, and optional ADMIN_EMAIL. Passwords are stored as hashes, never as plaintext. An existing PostgreSQL volume is not overwritten: the backend only replaces the untouched legacy quantdinger / 123456 administrator when a non-default administrator is explicitly configured. It never overwrites an account whose password was already changed, and it refuses to promote an existing account that already uses the requested username.

Manual Docker deployments retain quantdinger / 123456 only for backward compatibility when the administrator variables are left at their defaults. This credential is not suitable for an internet-facing deployment; change it before first start or immediately after the first login. The one-command installer does not accept 123456 as the chosen password.

The Settings UI writes runtime configuration to /app/.env. In the GHCR stack this is the host backend.env; in a source deployment it is backend_api_python/.env. Current backend images automatically give runtime UID 10001 ownership and keep mode 600. Do not use chmod 755 or recursive 777: these files contain passwords and API keys, and 755 still does not grant write access to UID 10001 when root owns the file.

Verify write access with:

docker compose exec -u 10001:10001 -T backend \
  sh -c 'test -w /app/.env && echo writable=yes || echo writable=no'

The hardened production override intentionally mounts /app/.env read-only. When using docker-compose.production.yml, manage configuration on the host and recreate the services instead of saving it from the Settings UI. See the [English guide](docs/deployment/ADMINANDSETTINGSTROUBLESHOOTINGEN.md) or [中文指南](docs/deployment/ADMINANDSETTINGSTROUBLESHOOTINGCN.md) for legacy-image recovery and rootless/NFS notes.

Option B: source checkout

git clone https://github.com/OpenByteInc/QuantDinger.git
cd QuantDinger
cp backend_api_python/env.example backend_api_python/.env
cp .env.example .env

Before the first start, replace the example values in both environment files:

| File | Required production values | | --- | --- | | backend_api_python/.env | SECRET_KEY, CREDENTIAL_ENCRYPTION_KEY, ADMIN_USER, ADMIN_PASSWORD | | .env | POSTGRES_PASSWORD, REDIS_PASSWORD, CELERY_REDIS_PASSWORD, GRAFANA_ADMIN_PASSWORD |

Generate independent secrets with:

python -c "import secrets; print(secrets.token_hex(32))"

Start the core stack from local backend source:

docker compose up -d --build
docker compose ps

The base stack does not start Prometheus, Grafana, or Alertmanager. This keeps the default open-source installation smaller.

For detailed installation paths, Windows notes, China mirror settings, and PostgreSQL migration guidance, see [Installation troubleshooting](docs/deployment/INSTALLTROUBLESHOOTING.md) and the [cloud deployment guide](docs/deployment/CLOUDDEPLOYMENT_EN.md).

Production deployment

Validate secrets before starting a production stack:

python backend_api_python/scripts/check_production_config.py \
  --env-file .env \
  --env-file backend_api_python/.env

Start the hardened runtime with optional observability:

docker compose \
  -f docker-compose.yml \
  -f docker-compose.production.yml \
  -f docker-compose.observability.yml \
  up -d --build

Omit docker-compose.observability.yml when the host is resource-constrained or monitoring is provided externally.

Production rules:

• expose only a TLS reverse proxy on ports 80/443;
• keep PostgreSQL, both Redis instances, Prometheus, Grafana, and Alertmanager

off the public internet;

• do not deploy with example passwords or empty encryption keys;
• back up PostgreSQL and the durable redis-jobs volume;
• keep cache Redis disposable and never use it as the Celery broker;
• review worker health and application readiness after every deployment.

The full checklist is in [Production hardening](docs/deployment/PRODUCTION_HARDENING.md).

Local endpoints

All published ports bind to loopback by default.

| Service | Default URL | Purpose | | --- | --- | --- | | Web | | Desktop web client and same-origin API proxy. | | Mobile H5 | | Mobile web client and same-origin API proxy. | | Backend | | Direct API access and health endpoints. | | Grafana | | Dashboards; available only with the observability overlay. | | Prometheus | | Metrics storage and queries; optional. | | Alertmanager | | Alert grouping, silencing, and delivery; optional. |

Container-only ports such as the job Redis and exporters are not published to the host.

Observability

The monitoring stack is optional by design:

• Prometheus collects API, worker, PostgreSQL, and Redis metrics.
• Grafana turns those metrics into operator dashboards.
• Alertmanager groups alerts, manages silences, and sends notifications once

a receiver is configured.

Start it for local diagnostics without the production overlay:

docker compose \
  -f docker-compose.yml \
  -f docker-compose.observability.yml \
  up -d

Monitoring services stay on 127.0.0.1. Use a VPN, SSH tunnel, or authenticated reverse proxy for remote administration. See [Observability](docs/deployment/OBSERVABILITY.md) for dashboards, alerts, retention, and receiver configuration.

Security model

• Broker credentials and MFA secrets are encrypted with a stable

CREDENTIAL_ENCRYPTION_KEY.

• Agent tokens are hashed, scoped, rate-limited, and audit-logged.
• Agent trading is paper-only by default; live access requires both token and

server-side authorization.

• Long-running strategy ownership uses leases, heartbeats, and fencing tokens.
• Production containers run without root privileges or Linux capabilities.
• Host port defaults are loopback-only; public access should terminate at a TLS

reverse proxy.

Report vulnerabilities privately according to [SECURITY.md](SECURITY.md). Do not include credentials, account data, or exploitable details in public issues.

Strategy and integration surfaces

| Area | Current surface | | --- | --- | | Indicators | Python chart overlays, markers, bands, and signals. | | Strategies | Strategy API V2 intents, sizing, risk, backtests, and live runtime. | | Crypto | Binance, OKX, Bitget, Bybit, Gate, HTX, Coinbase Exchange, Kraken, and adapter extensions. | | Traditional brokers | IBKR and Alpaca workflows. | | AI providers | OpenRouter, OpenAI-compatible APIs, Google, DeepSeek, Grok, MiniMax, and custom endpoints. | | Automation | Human API, Agent Gateway, MCP server, Celery jobs, schedules, and notifications. |

Start with the [Indicator guide](docs/trading/INDICATORDEVGUIDE.md), [Strategy guide](docs/trading/STRATEGYDEVGUIDE.md), and [Extension guide](docs/architecture/EXTENSION_GUIDE.md).

AI agents and MCP

The Agent Gateway is exposed under /api/agent/v1. The included MCP server lets clients such as Cursor, Claude Code, and Codex call approved tools without receiving broker credentials or administrator JWTs.

Live trading through an agent requires all of the following:

1. a token with trading scope;
2. paper_only=false on that token;
3. AGENT_LIVE_TRADING_ENABLED=true on the server;
4. operator-configured limits and allowlists.

See [MCP setup](docs/agent/MCPSETUP.md), [Agent quick start](docs/agent/AGENTQUICKSTART.md), and the [Agent OpenAPI document](docs/agent/agent-openapi.json).

Development

Backend development uses Python 3.12:

cd backend_api_python
python -m venv .venv
python -m pip install -r requirements-dev.txt
python -m pytest -m "not integration and not stress" --ignore=tests/release_gate -q
ruff check app scripts tests

Useful repository checks:

python scripts/check_version.py
python scripts/check_mojibake.py
docker compose -f docker-compose.yml config -q
docker compose -f docker-compose.yml -f docker-compose.production.yml -f docker-compose.observability.yml config -q

API changes should follow [API conventions](docs/architecture/API_CONVENTIONS.md), update the OpenAPI artifact when required, and pass the compatibility workflow.

Repository layout

This repository contains the backend, worker processes, deployment definitions, operations configuration, documentation, and MCP server. The desktop and mobile client source code live in separate repositories; this repository consumes their published images in the Compose stacks.

QuantDinger/
|-- .github/workflows/                 CI, security, compatibility, and release checks
|-- backend_api_python/                Backend application and all backend processes
|   |-- app/
|   |   |-- __init__.py                Flask application factory and core wiring
|   |   |-- startup.py                 Process-aware startup hooks and service singletons
|   |   |-- celery_app.py              Celery application and task registration
|   |   |-- commands/                  Migration, scheduler, trading, and health entrypoints
|   |   |-- config/                    Environment-backed database, Redis, and provider config
|   |   |-- routes/                    Human HTTP API route facades
|   |   |   `-- agent_v1/              Scoped Agent Gateway API under /api/agent/v1
|   |   |-- openapi/                   OpenAPI schemas, tags, registration, and export support
|   |   |-- services/                  Domain workflows and third-party integrations
|   |   |   |-- backtest_engine/       Backtest execution components
|   |   |   |-- live_trading/          Normalized crypto exchange adapters
|   |   |   |-- alpaca_trading/        Alpaca broker integration
|   |   |   |-- ibkr_trading/          Interactive Brokers integration
|   |   |   |-- strategy_runtime/      Strategy signals, intents, execution, and state
|   |   |   `-- strategy_v2/           Versioned strategy contracts and runtime services
|   |   |-- data_sources/              Raw market-data source adapters
|   |   |-- data_providers/            Aggregated market, macro, news, and sentiment providers
|   |   |-- markets/                   Market and symbol normalization
|   |   |-- tasks/                     Finite, retryable Celery jobs
|   |   |-- workers/                   Long-lived worker process shells
|   |   |-- runtime/                   Process-role and ownership helpers
|   |   |-- observability/             Request context, metrics, and HTTP instrumentation
|   |   `-- utils/                     Shared low-level database, cache, auth, and logging helpers
|   |-- migrations/

…

## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [OpenByteInc](https://github.com/OpenByteInc)
- **Source:** [OpenByteInc/QuantDinger](https://github.com/OpenByteInc/QuantDinger)
- **License:** Apache-2.0
- **Homepage:** https://www.quantdinger.com

Install and usage instructions live in the source repository linked above.