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Habinar

MCP Paradex Server

by Habinar

paradex_open_orders

Read-only

Monitor active orders to track execution status, verify prices and quantities, and manage trading strategies on the Paradex perpetual futures platform.

Instructions

Monitor your active orders to track execution status and manage your trading strategy.

Use this tool when you need to:
- Check which of your orders are still pending execution
- Verify limit order prices and remaining quantities
- Determine which orders might need cancellation or modification
- Get a complete picture of your current market exposure

Keeping track of your open orders is essential for effective order management
and avoiding duplicate or conflicting trades.

Example use cases:
- Checking if your limit orders have been partially filled
- Verifying that a recently placed order was accepted by the exchange
- Identifying stale orders that should be canceled or modified
- Getting a consolidated view of all pending orders across markets

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
market_idNoFilter by market.ALL
limitNoLimit the number of results to the specified number.
offsetNoOffset the results to the specified number.

Implementation Reference

  • The handler function for the paradex_open_orders tool. It authenticates with Paradex client, fetches open orders optionally filtered by market, validates and sorts them by creation time, applies pagination with limit and offset, and returns a structured response including schema and metadata.
    @server.tool(name="paradex_open_orders", annotations=ToolAnnotations(readOnlyHint=True))
    async def get_open_orders(
        market_id: Annotated[str, Field(default="ALL", description="Filter by market.")],
        limit: Annotated[
            int,
            Field(
                default=10,
                gt=0,
                le=100,
                description="Limit the number of results to the specified number.",
            ),
        ],
        offset: Annotated[
            int,
            Field(
                default=0,
                ge=0,
                description="Offset the results to the specified number.",
            ),
        ],
        ctx: Context = None,
    ) -> dict:
        """
        Monitor your active orders to track execution status and manage your trading strategy.
    
        Use this tool when you need to:
        - Check which of your orders are still pending execution
        - Verify limit order prices and remaining quantities
        - Determine which orders might need cancellation or modification
        - Get a complete picture of your current market exposure
    
        Keeping track of your open orders is essential for effective order management
        and avoiding duplicate or conflicting trades.
    
        Example use cases:
        - Checking if your limit orders have been partially filled
        - Verifying that a recently placed order was accepted by the exchange
        - Identifying stale orders that should be canceled or modified
        - Getting a consolidated view of all pending orders across markets
        """
        client = await get_authenticated_paradex_client()
        params = {"market": market_id} if market_id != "" and market_id != "ALL" else None
        response = client.fetch_orders(params=params)
        if "error" in response:
            ctx.error(f"Error fetching open orders: {response['error']}")
            raise Exception(response["error"])
        orders = order_state_adapter.validate_python(response["results"])
        sorted_orders = sorted(orders, key=lambda x: x.created_at)
        result_orders = sorted_orders[offset : offset + limit]
        result = {
            "description": OrderState.__doc__.strip() if OrderState.__doc__ else None,
            "fields": OrderState.model_json_schema(),
            "results": result_orders,
            "total": len(sorted_orders),
            "limit": limit,
            "offset": offset,
        }
        return result
  • The @server.tool decorator registers the paradex_open_orders tool with readOnlyHint=True.
    @server.tool(name="paradex_open_orders", annotations=ToolAnnotations(readOnlyHint=True))
  • Schema reference for paradex_open_orders output provided via get_filters_model tool, using OrderState.model_json_schema() for type validation and documentation.
    tool_descriptions = {
        "paradex_markets": models.MarketDetails.model_json_schema(),
        "paradex_market_summaries": models.MarketSummary.model_json_schema(),
        "paradex_open_orders": models.OrderState.model_json_schema(),
        "paradex_orders_history": models.OrderState.model_json_schema(),
        "paradex_vaults": models.Vault.model_json_schema(),
        "paradex_vault_summary": models.VaultSummary.model_json_schema(),
    }
  • TypeAdapter for list[OrderState] used to validate the API response in the handler.
    order_state_adapter = TypeAdapter(list[OrderState])
Behavior4/5

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

The annotations indicate readOnlyHint=true, which the description aligns with by describing monitoring/checking functions. The description adds valuable behavioral context beyond annotations, such as the tool's role in order management, avoiding duplicate trades, and use cases like checking partial fills or identifying stale orders, though it doesn't specify rate limits or authentication needs.

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 a clear opening sentence, bulleted usage guidelines, and example use cases. It's appropriately sized for the tool's complexity, though the final paragraph ('Keeping track...') is somewhat redundant with earlier content, slightly reducing efficiency.

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, read-only operation, no output schema), the description provides good contextual completeness. It explains the tool's purpose, usage, and behavioral context effectively, though it could benefit from mentioning the lack of output schema or typical response format for better agent guidance.

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 fully documents the three parameters (market_id, limit, offset). The description doesn't add any parameter-specific semantics beyond what's in the schema, such as explaining how filtering by market_id works in practice or the implications of limit/offset for pagination.

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 as monitoring active orders to track execution status and manage trading strategy. It uses specific verbs like 'monitor', 'track', and 'manage' with the resource 'active orders', and distinguishes itself from siblings like paradex_orders_history (historical orders) and paradex_order_status (single order status).

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 usage guidelines with a bulleted list of when to use this tool (e.g., 'Check which of your orders are still pending execution', 'Verify limit order prices and remaining quantities'). It implicitly distinguishes from alternatives by focusing on active orders, unlike paradex_orders_history for historical data or paradex_order_status for individual order details.

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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