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Compute Canadian ACB, capital gains, and superficial losses from trade history.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "acb-tax-mcp" yet — see the docs or source repo.
Using the following Canadian trade history, calculate the adjusted cost base (ACB) and capital gains, and return structured JSON: Buy 2024-01-10 100 shares of XYZ @ CAD 20; Buy 2024-03-05 50 shares of XYZ @ CAD 24; Sell 2024-06-18 80 shares of XYZ @ CAD 30.
A JSON result containing average cost, realized capital gain, and remaining position cost details.
Analyze whether this trade set triggers a Canadian superficial loss and output structured JSON: 2024-02-01 Buy 100 shares of ABC @ CAD 50; 2024-03-01 Sell 100 shares of ABC @ CAD 40; 2024-03-15 Buy 100 shares of ABC @ CAD 42.
A JSON response showing whether a superficial loss exists, which trades are involved, and any related cost adjustments.
Process the following trades in chronological order, calculate ACB and capital gains for each sale, and return a structured JSON summary: TSX:DEF 2024-01-08 Buy 200 shares @ CAD 10; 2024-04-10 Sell 50 shares @ CAD 14; 2024-07-22 Buy 80 shares @ CAD 11; 2024-09-30 Sell 100 shares @ CAD 13.
A JSON summary with per-sale tax calculations and the final remaining position cost basis.
Investment researchers or data analysts can feed trade history into this tool to calculate ACB and capital gains in a Canadian tax context. It is useful when replacing manual spreadsheet work.
When there are many trades or closely timed transactions, users can use it to check for superficial losses. The tool returns structured results based on the trade history for easier review.
Developers can integrate this MCP server into AI or workflow systems so the model outputs ACB, capital gains, and related detection results in consistent JSON. This makes downstream processing easier.
It is an MCP server that computes Canadian adjusted cost base (ACB) and capital gains from trade history. It also supports average-cost tracking and superficial-loss detection, returning structured JSON.
Based on the description, it needs trade history as input. To get meaningful results, you would typically provide buy and sell records and related trade details.
The provided material does not include installation steps, dependencies, or key requirements. See the source repository for implementation details.
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