Jinny supports controlled TradingIQ analysis

Trading availability is credential-aware. The live surface you see depends on configured venues, build profile, and registration mode.

Trading Hub

Trading Hub is SindByte's operator surface for paper-first AI-assisted trading: scan markets, compare signals, review MultiVote and Consensus output, and only graduate toward live execution when the workflow is ready.

12 venues
Paper-first
Scanner ranking
5-expert MultiVote
Learning + AAR
Credential verification

Trading Hub sits next to the audited MCP surface and the live catalog can expose more or fewer trading routes depending on which APIs are configured and which registration filters are active.

Download SindByte Trading Workflows Setup Notes Go to the MCP server
What it is
The trading operator surface of SindByte: scan markets, compare signals and run paper sessions with AI support. 12 venues are listed.
Who it is for
For anyone who wants to test AI-assisted trading ideas in paper mode first and manages the credentials of their exchanges or brokers themselves.
Requirements
SindByte (Windows 10 or 11, 4GB RAM minimum, about 50MB disk space, MCP-capable AI client). Each venue needs its own credentials; without valid credentials a venue stays inactive. Trading carries real financial risk, see the risk note.
How to get it
Part of SindByte: ZIP package via the download button.
Cost
Private, non-commercial use is free. Business, team, and commercial usage goes through Smart Package Robot or by email to info@it-berater.org.
Kraken Trade Console (screenshot)
Screenshot of the Kraken Trade Console. Use this family of forms for credential checks, market review, paper sessions, and post-trade learning.

Supported Venues

This page reflects the audited 12-venue surface. Individual venues can still stay hidden or inactive at runtime until valid credentials exist.

KrakenBinanceCoinbaseOKX KuCoinBitgetByBitBitpanda AlpacaIGInteractive BrokersPolygon

Trading forms in SindByte (screenshots)

Kraken Trade Console screenshot Trade Console

Venue selection, risk framing, strategy fields, and session actions in the live trading shell.

Manual Trading Platform screenshot Manual Trading

Paper-first execution surface for controlled entries, exits, and repeatable session review.

Kraken Learning Lab screenshot Learning Lab

After-action review and learning capture so trade ideas turn into documented policy instead of memory.

TradingIQ and TradingAI Stack

TradingIQ::Scanner

Scan and rank markets by RSI, ADX, volume, and spread (top-N selection) so the session starts from a narrowed candidate list instead of raw venue noise.

TradingIQ::MultiVote

Run a 5-expert vote (Technical, Macro, Risk, Quant, Contrarian) over one candidate idea to compare the views before acting.

TradingIQ::Consensus

Request a deeper individual analysis with a strategy preset, explicit risk framing, and clean closing output when a quick vote is not enough.

TradingIQ::Learning

Review paper results, store observations, define criteria for a later live transition, and turn each session into a repeatable learning loop instead of isolated one-off trades.

TradingAI::DecisionMenu v2

Keep the session alive through a circular decision flow with 12 options, explicit next actions, persistent context, and clean session end points.

APIV_Verify*

Verify exchange and data-provider credentials live and report the status, so you know whether the runtime can publish and use a given route safely.

DecisionMenu v2 Session Loop

Info branch: Scan markets, analyze a pair, enrich the idea with web research, and call TradingIQ when simple chart impressions are not enough.
Account branch: Inspect balances and positions and validate credentials before you size anything. The session stays grounded in what the account can actually support.
Learning branch: Record observations, query prior learnings, and backfill AAR entries from paper rounds so repeated setups can be compared over time.
Trade branch: Execute, close, wait, or end the session cleanly. The menu keeps the decision process explicit instead of letting the model improvise hidden state.

Paper-First Operational Path

1. Verify the venue key, switch to paper mode (paper_mode), and define the session risk budget before scanning.
2. Use Scanner to shortlist opportunities, then run MultiVote or Consensus on the strongest candidate.
3. Simulate the trade, record the paper result, and generate an after-action review so the next session has real feedback.
4. Only consider live graduation after repeated paper sessions with documented behavior and restricted API permissions.
Risk and catalog note: Trading carries real financial risk. Always test new strategies in paper mode first, store venue keys with minimal permissions, and expect the runtime-visible trading catalog to differ between machines depending on configured credentials and registration policy.

Need help with setup and operation?

For companies we handle installation, model selection matched to your hardware, safe permissions and team training on request. Start with a free 20-minute intro call.

Set up MCP server & local AI Local AI with LM Studio

Continue

Go to the manual for setup, or use the workflow page for concrete trading, timer, and review sequences that combine Trading Hub with the wider SindByte platform.

Manual Workflows MCP Server