Marketing Team
Integrating broker systems with our API – a CRM, a sales panel, or an executive dashboard – tends to be time-intensive. Even when the requirements are clear, delivery slows down because of the process mechanics: reading documentation endpoint by endpoint, handling authentication, mapping fields, and testing each request separately. The result is predictable, with even simple integrations turning into multi-week efforts before the first usable output is delivered. Our AI Skills for Broker API and CRM API are designed to remove that friction.
What Are Match-Trader API Skills?
In practice, a Skill is a ready-to-use, structured “operating manual” for our API that you connect to Claude (or any other AI that supports this format). From that point on, the AI understands the integration end-to-end: how to authenticate, which endpoints are available, what data they return, and how they relate to each other.
Traditional integrations are constructed bottom-up: implement one endpoint, read its documentation, write code, test it, move to the next endpoint, and repeat until everything comes together into a complete solution. With a Skill, this workflow shifts. Instead of integrating endpoints one by one, you describe what you want to achieve, and Claude uses the Skill to assemble the full integration in one pass – selecting the right endpoints, handling authentication, and combining data into a consistent model. That’s how the effort shifts from building the integration to reviewing it. What you get is a complete solution that can be verified, adjusted, and polished if needed.
Combine Multiple Systems in One Analysis
All brokers operate multiple systems that include data about the same client – a CRM on one side and a sales system or trading platform on the other. With the Broker API and CRM API Skills, Claude integrates with both at the same time, pulling client records from the CRM, matching them with data from the trading or sales system, and performing higher-level analysis such as trades per client, typical position sizes, and implications for sales or retention.
The same logic works for other types of questions, including identifying the most traded instruments, improving sales settlements/commissions, or standardizing performance metrics. With this approach, it’s enough to describe to the AI how to calculate something, and then the finished integration can be automated to run cyclically on its own, without manually rebuilding the workflow each time.
Sales Reporting Without a Custom Development Project
A common starting point is straightforward: the sales team needs a report that isn’t currently available in the system. Instead of opening an IT ticket and waiting for engineering capacity, a user equipped with the Skill can simply describe the required output to the AI. Claude then connects to the Broker API, pulls the relevant data, and produces a ready-to-use report.
What previously required a development team and an integration written from scratch can now be created independently in a single guided session with Claude. At the end, the IT team reviews the AI-generated integration, applies any necessary adjustments, and once it is validated, finalizes it for use.
Client-Level Hedging Analysis for A-Book/B-Book Decisions
Selective hedging is often implemented as an all-clients or no-clients policy, largely because making it work at a granular level requires reliable integrations and solid data analysis. With the Skill connected to our API, Claude can build the necessary data flows, link client profiles with position data, and produce an analysis of profitability and decision criteria under defined conditions. This enables client-level analysis without initiating a separate, dedicated integration project solely to support hedging decisions.
Identifying Data Inconsistencies Across Systems
Discrepancies between systems and settlement results typically require manual reconciliation across multiple data sources to identify where values diverge. With the Skill, Claude can connect to the relevant systems and help identify inconsistencies, reducing the time and effort required for manual verification.
Support Workflow Automation
A significant share of support tickets relates to questions such as why a position was closed. In many cases, the underlying reason is margin-related – for example, insufficient free funds triggering a forced close-out. Using the Skill, it becomes much simpler to build automations that pull the relevant context from the Broker API and generate a clear explanation of what happened. This workflow can be drafted directly with the AI and then reviewed and finalized, rather than delivered as a separate development project.
Faster MVP Delivery for Internal Tools and Dashboards
The most practical benefit of the Skill is faster delivery of a first working version. When integration with our API is no longer a standalone project, initial versions of dashboards, reports, and tools can be created noticeably faster. You can define the concept, generate an integration with AI and the Skills, validate that it meets the need, and only then pass it to developers for proper production implementation.
Three Match-Trader Integrations Built with API Skills
We validated this approach with three working dashboards “vibe-coded” with Claude using our Broker API Skill. In each case, the integration was assembled end-to-end through an AI-guided workflow – without spending time navigating documentation page by page or implementing the entire API layer from scratch.
Most Traded Instruments
A leaderboard of the most traded instruments with a time-range selector (1D / 1W / 1M). Each row can be expanded to show full instrument statistics, including win rate, total P/L, volume, the buy/sell split, paid commissions, and accrued swap. This is a typical sales request that previously required a dedicated integration effort.
MT Prop Support Dashboard for Prop Accounts
A support-facing view for searching and reviewing prop challenge accounts by client login or email. Each account presents the full picture: CRM data (name, email, CRM UUID), trading account parameters (group, leverage, account type), current financial status (balance, equity, profit, margin, free funds), challenge progress against targets (profit target, max loss, max daily loss), and account status (in challenge, funded, or failed).
For failed accounts, the dashboard automatically provides a failure-state snapshot: starting balance, equity at the point of failure, daily and maximum loss limits, and the specific rule breached (e.g., “Max Daily Loss Reached”). This is a representative example of a combined CRM API + Broker API integration produced in a single AI session, rather than delivered in separate project phases.
Prediction Market Trader Leaderboard
A ranking of Prediction Market traders with selectable time ranges and drill-down views per user: transaction count, total stake, net P/L, and ROI%. The expanded view lists individual trades, including the underlying event (from FX and commodities to sports outcomes), settlement date, stake, and result – together with an explanation of the ROI aggregation logic to keep calculations consistent.
How to Get Started with Match-Trader API Skills
The Broker API and CRM API Skills are already available for use with Claude. If your team frequently runs into gaps such as missing integrations or slow time-to-connection, it is worth prototyping the full integration with Claude first before submitting a ticket to IT. Contact us and learn more about the solution.
