paradex_account_fills
Analyze executed trades to review trading history, calculate average entry prices, track realized PnL, and verify order execution details for performance evaluation.
Instructions
Analyze your executed trades to evaluate performance and execution quality.
Use this tool when you need to:
- Review your trading history across specific markets
- Calculate your average entry price for multi-fill positions
- Analyze execution quality compared to intended prices
- Track realized PnL from completed trades
- Verify order execution details for reconciliation
Detailed fill information is essential for performance analysis and
understanding how your orders were actually executed.
Example use cases:
- Calculating volume-weighted average price (VWAP) of your entries
- Analyzing execution slippage from your intended prices
- Reviewing trade history for tax or accounting purposes
- Tracking commission costs across different markets
- Identifying which of your strategies produced the best executionInput Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| market_id | Yes | Filter by market ID. | |
| start_unix_ms | Yes | Start time in unix milliseconds. | |
| end_unix_ms | Yes | End time in unix milliseconds. |
Implementation Reference
- src/mcp_paradex/tools/account.py:88-127 (handler)The handler function decorated with @server.tool(name="paradex_account_fills"). It fetches fills from the Paradex client for the specified market and time range, validates using fill_adapter (TypeAdapter(list[Fill])), and returns a structured response including description, schema, and results.
@server.tool(name="paradex_account_fills") async def get_account_fills( market_id: Annotated[str, Field(description="Filter by market ID.")], start_unix_ms: Annotated[int, Field(description="Start time in unix milliseconds.")], end_unix_ms: Annotated[int, Field(description="End time in unix milliseconds.")], ctx: Context = None, ) -> dict: """ Analyze your executed trades to evaluate performance and execution quality. Use this tool when you need to: - Review your trading history across specific markets - Calculate your average entry price for multi-fill positions - Analyze execution quality compared to intended prices - Track realized PnL from completed trades - Verify order execution details for reconciliation Detailed fill information is essential for performance analysis and understanding how your orders were actually executed. Example use cases: - Calculating volume-weighted average price (VWAP) of your entries - Analyzing execution slippage from your intended prices - Reviewing trade history for tax or accounting purposes - Tracking commission costs across different markets - Identifying which of your strategies produced the best execution """ client = await get_authenticated_paradex_client() params = {"market": market_id, "start_at": start_unix_ms, "end_at": end_unix_ms} response = client.fetch_fills(params) if "error" in response: await ctx.error(response) raise Exception(response["error"]) fills = fill_adapter.validate_python(response["results"]) results = { "description": Fill.__doc__.strip() if Fill.__doc__ else None, "fields": Fill.model_json_schema(), "results": fills, } return results - Pydantic TypeAdapter for list[Fill], used to validate the response data. Fill is imported from mcp_paradex.models.
fill_adapter = TypeAdapter(list[Fill]) - src/mcp_paradex/tools/account.py:88-88 (registration)The @server.tool decorator registers the get_account_fills function as the MCP tool named "paradex_account_fills".
@server.tool(name="paradex_account_fills")