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Habinar

MCP Paradex Server

by Habinar

paradex_account_summary

Check your account's current financial status, including balances, margin utilization, P&L, and liquidation risk, to inform trading decisions.

Instructions

Get a snapshot of your account's current financial status and trading capacity.

Use this tool when you need to:
- Check your current available and total balance
- Understand your margin utilization and remaining trading capacity
- Verify your account health and distance from liquidation
- Get an overview of realized and unrealized P&L

This provides the essential financial information needed to make informed
trading decisions and manage risk appropriately.

Example use cases:
- Checking available balance before placing new orders
- Monitoring account health during volatile market conditions
- Assessing realized and unrealized P&L for performance tracking
- Verifying margin requirements and utilization

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function decorated with @server.tool that implements the paradex_account_summary tool. It fetches the account data via API and validates it using the AccountSummary schema.
    @server.tool(name="paradex_account_summary")
    async def get_account_summary(ctx: Context) -> dict:
        """
        Get a snapshot of your account's current financial status and trading capacity.
    
        Use this tool when you need to:
        - Check your current available and total balance
        - Understand your margin utilization and remaining trading capacity
        - Verify your account health and distance from liquidation
        - Get an overview of realized and unrealized P&L
    
        This provides the essential financial information needed to make informed
        trading decisions and manage risk appropriately.
    
        Example use cases:
        - Checking available balance before placing new orders
        - Monitoring account health during volatile market conditions
        - Assessing realized and unrealized P&L for performance tracking
        - Verifying margin requirements and utilization
        """
        client = await get_authenticated_paradex_client()
        response = await api_call(client, "account")
        result = {
            "description": AccountSummary.__doc__.strip() if AccountSummary.__doc__ else None,
            "fields": AccountSummary.model_json_schema(),
            "results": account_summary_adapter.validate_python(response),
        }
        return result
  • Pydantic BaseModel defining the schema for the account summary response data, used for validation in the tool handler.
    class AccountSummary(BaseModel):
        """Model representing an account summary response from Paradex."""
    
        account: Annotated[str, Field(description="User's starknet account")]
        account_value: Annotated[str, Field(description="Current account value [with unrealized P&Ls]")]
        free_collateral: Annotated[
            str,
            Field(
                description="Free collateral available (Account value in excess of Initial Margin required)"
            ),
        ]
        initial_margin_requirement: Annotated[
            str, Field(description="Amount required to open trade for the existing positions")
        ]
        maintenance_margin_requirement: Annotated[
            str, Field(description="Amount required to maintain exisiting positions")
        ]
        margin_cushion: Annotated[
            str, Field(description="Acc value in excess of maintenance margin required")
        ]
        seq_no: Annotated[
            int,
            Field(
                description="Unique increasing number (non-sequential) that is assigned to this account update. Can be used to deduplicate multiple feeds"
            ),
        ]
        settlement_asset: Annotated[str, Field(description="Settlement asset for the account")]
        status: Annotated[str, Field(description="Status of the acc - like ACTIVE, LIQUIDATION")]
        total_collateral: Annotated[str, Field(description="User's total collateral")]
        updated_at: Annotated[int, Field(description="Account last updated time")]
  • The @server.tool decorator registers the paradex_account_summary tool with the MCP server.
    @server.tool(name="paradex_account_summary")
  • TypeAdapter for AccountSummary used to validate the API response in the handler.
    account_summary_adapter = TypeAdapter(AccountSummary)
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It effectively communicates that this is a read-only operation for financial data (implied by 'Get a snapshot'), but lacks details on rate limits, authentication requirements, or potential data freshness issues. It adds value by explaining the type of information returned but doesn't fully cover behavioral traits.

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 well-structured with clear sections (purpose, usage guidelines, example use cases) and front-loaded key information. While slightly verbose, every sentence adds value by clarifying the tool's role and practical applications without redundancy.

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 complexity (financial summary with no parameters) and lack of annotations/output schema, the description provides comprehensive context about what information is returned and when to use it. It could be more complete by specifying the exact data fields returned, but it adequately covers the essential aspects for informed usage.

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

Parameters4/5

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

The tool has 0 parameters with 100% schema description coverage. The description appropriately doesn't discuss parameters, maintaining focus on the tool's purpose and usage. This meets the baseline of 4 for zero-parameter tools, as no parameter information is needed.

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

Purpose5/5

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

The description clearly states the tool's purpose with specific verbs ('Get a snapshot') and resources ('account's current financial status and trading capacity'), distinguishing it from siblings like paradex_account_fills or paradex_account_positions by focusing on overall financial health rather than specific transactions or positions.

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 explicitly lists four use cases (e.g., 'Checking available balance before placing new orders') and provides a clear 'Use this tool when you need to' section with bullet points, offering strong guidance on when to use this tool versus alternatives like paradex_account_funding_payments or paradex_account_transactions.

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

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