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Habinar

MCP Paradex Server

by Habinar

paradex_account_funding_payments

Analyze funding payment history to calculate costs, assess P&L impact, and plan trading strategies for perpetual futures positions.

Instructions

Track your funding payment history to understand its impact on P&L.

Use this tool when you need to:
- Calculate total funding costs or gains for a position
- Analyze how funding has affected your overall performance
- Plan position timing around funding payment schedules
- Compare funding costs across different markets
- Account for funding in your trading strategy profitability

Funding payments can significantly impact perpetual futures trading P&L,
especially for longer-term positions or in markets with volatile funding rates.

Example use cases:
- Calculating the total funding component of your P&L
- Comparing funding costs against trading profits
- Planning position entries/exits around funding payment times
- Identifying markets where funding has been consistently favorable
- Reconciling funding payments for accounting purposes

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
market_idNoFilter by market ID.
start_unix_msYesStart time in unix milliseconds.
end_unix_msYesEnd time in unix milliseconds.

Implementation Reference

  • The handler function for the 'paradex_account_funding_payments' tool. It is registered via the @server.tool decorator and implements the logic to fetch funding payments from the Paradex client using provided parameters (optional market_id and required time range). The function parameters with Annotated types define the input schema. It returns the raw API response.
    @server.tool(name="paradex_account_funding_payments")
    async def get_account_funding_payments(
        market_id: Annotated[str | None, Field(default=None, 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:
        """
        Track your funding payment history to understand its impact on P&L.
    
        Use this tool when you need to:
        - Calculate total funding costs or gains for a position
        - Analyze how funding has affected your overall performance
        - Plan position timing around funding payment schedules
        - Compare funding costs across different markets
        - Account for funding in your trading strategy profitability
    
        Funding payments can significantly impact perpetual futures trading P&L,
        especially for longer-term positions or in markets with volatile funding rates.
    
        Example use cases:
        - Calculating the total funding component of your P&L
        - Comparing funding costs against trading profits
        - Planning position entries/exits around funding payment times
        - Identifying markets where funding has been consistently favorable
        - Reconciling funding payments for accounting purposes
        """
        client = await get_authenticated_paradex_client()
        params = {"market": market_id, "start_at": start_unix_ms, "end_at": end_unix_ms}
        # Remove None values from params
        params = {k: v for k, v in params.items() if v is not None}
        response = client.fetch_funding_payments(params)
        return response

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It discloses that the tool tracks funding payment history and explains why this matters for P&L calculations. However, it doesn't describe behavioral traits like whether this is a read-only operation, what permissions are needed, rate limits, pagination, or error conditions. The description adds useful context about funding's impact but lacks operational details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and well-structured with clear sections: purpose statement, when-to-use bullet points, context about funding impact, and example use cases. Every sentence adds value, though the example use cases section somewhat overlaps with the usage guidelines. The description could be slightly more concise by integrating these sections.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (3 parameters, no annotations, no output schema), the description provides good contextual completeness. It explains the purpose, usage scenarios, and importance of funding payments for trading. However, without annotations or output schema, it doesn't cover behavioral aspects like response format, error handling, or authentication requirements, which would be helpful for a financial data tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all three parameters (market_id, start_unix_ms, end_unix_ms) with descriptions. The description doesn't add any parameter-specific information beyond what's in the schema. It implies filtering by market and time ranges through the use cases but doesn't provide additional syntax or format details. Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose as tracking funding payment history to understand its impact on P&L, which is specific (verb+resource). It distinguishes from siblings like paradex_account_summary or paradex_account_transactions by focusing specifically on funding payments rather than general account data. However, it doesn't explicitly contrast with paradex_funding_data, which might be a related sibling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance with a bulleted list of when to use this tool ('Calculate total funding costs...', 'Analyze how funding has affected...', etc.). It gives clear context about funding payments impacting perpetual futures trading P&L, especially for longer-term positions. The example use cases section further reinforces appropriate usage scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.