Running TradeCanvas as a service, AI Code Tools

TradeCanvas Agency Implementation, AI-Powered Trading Chart Delivery

Learn how to deliver interactive candlestick charts and AI-agent-integrated trading applications to fintech clients using TradeCanvas. This course covers exchange adapter setup, MCP server configuration for Claude integration, annotation layer customization, and productizing chart delivery as a retainer service for Asia-Pacific trading platforms.

Open the decision record for TradeCanvas

What does running TradeCanvas for clients commit you to?

Published figures for this service. Blank fields are not published.

Monthly tool cost
Not published
Time to first value
Not published
Payback
Not modeled
Guided implementation
8 hours

Is TradeCanvas worth running as a client service?

TradeCanvas is an open-source MIT-licensed library with a genuine MCP differentiator for agent-driven chart workflows, but it requires front-end engineering and client-supplied data feeds. No vendor cost basis or market rate evidence is published, so agency economics remain unknown until labor, client price and usage are measured.

An agency-fit judgement for reselling this service. It is separate from the tool description on the decision record.

Before you start

What has to be in place before the first client engagement.

Tools and subscriptions

  • npm access to install @tradecanvas/chart and related packages
  • An exchange adapter or custom REST market data endpoint for candles and tickers
  • React, Vue or Svelte front-end stack to host the chart components
  • An MCP-compatible AI client if agent-driven chart configuration is in scope

People and inputs

  • A front-end engineer with trading or fintech charting experience, given the high setup complexity
  • Access to KRX, NXT or Upbit market definitions documentation for market rule configuration
  • A locale testing plan covering number and volume formatting for each client market

Estimated investment: TradeCanvas is MIT-licensed open-source with no published vendor cost; the agency's investment is engineering labor and any exchange data feed or hosting costs, which must be estimated by the agency.

Included with the course

7 working documents for delivering this service.

  • TradeCanvas Project Scope Worksheetworksheet
  • Exchange Adapter Configuration Checklist (KRX, NXT, Upbit)checklist
  • MCP Server Setup and Claude Integration SOPsop
  • Trading Annotation Layer Implementation Templatetemplate
  • Multi-Locale Chart Formatting Guide (APAC Markets)guide
  • AI Agent Chart State Validation Workflowsop
  • Client Onboarding and Chart Customization Checklistchecklist

Listed by name. These documents are not yet published as individual downloads.