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norman-finance

Norman Finance MCP Server

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list_invoices

Retrieve and filter invoices on the Norman Finance MCP Server based on status, client name, date range, and limit. Simplify financial tracking and reporting.

Instructions

List invoices with optional filtering.

Args:
    status: Filter by invoice status (draft, pending, sent, paid, overdue, uncollectible)
    name: Filter by invoice (client) name
    from_date: Filter invoices created after this date (YYYY-MM-DD)
    to_date: Filter invoices created before this date (YYYY-MM-DD)
    limit: Maximum number of invoices to return (default 100)
    
Returns:
    List of invoices matching the criteria

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
from_dateNo
limitNo
nameNo
statusNo
to_dateNo

Implementation Reference

  • The MCP tool handler for 'list_invoices'. Decorated with @mcp.tool(), it retrieves a list of invoices from the Norman API endpoint, applying optional filters for status, name, date range, and limit.
    @mcp.tool()
    async def list_invoices(
        ctx: Context,
        status: Optional[str] = None,
        name: Optional[str] = None,
        from_date: Optional[str] = None,
        to_date: Optional[str] = None,
        limit: Optional[int] = 100
    ) -> Dict[str, Any]:
        """
        List invoices with optional filtering.
        
        Args:
            status: Filter by invoice status (draft, pending, sent, paid, overdue, uncollectible)
            name: Filter by invoice (client) name
            from_date: Filter invoices created after this date (YYYY-MM-DD)
            to_date: Filter invoices created before this date (YYYY-MM-DD)
            limit: Maximum number of invoices to return (default 100)
            
        Returns:
            List of invoices matching the criteria
        """
        api = ctx.request_context.lifespan_context["api"]
        company_id = api.company_id
        
        if not company_id:
            return {"error": "No company available. Please authenticate first."}
        
        invoices_url = urljoin(
            config.api_base_url, 
            f"api/v1/companies/{company_id}/invoices/"
        )
        
        # Build query parameters
        params = {}
        if status:
            params["status"] = status
        if from_date:
            params["dateFrom"] = from_date
        if to_date:
            params["dateTo"] = to_date
        if limit:
            params["limit"] = limit
        if name:
            params["name"] = name
        
        return api._make_request("GET", invoices_url, params=params) 
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions filtering and a default limit, but lacks critical details: whether this is a read-only operation, if it requires authentication, pagination behavior, rate limits, error conditions, or what happens when no filters are applied. For a list tool with 5 parameters, this leaves significant gaps in understanding how the tool behaves.

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

Conciseness5/5

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

The description is efficiently structured with a brief purpose statement followed by well-organized parameter and return sections. Every sentence earns its place by providing necessary information without redundancy. The formatting with clear headings makes it easy to parse.

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

Completeness3/5

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

Given the tool's moderate complexity (5 parameters, no output schema, no annotations), the description is partially complete. It excels at parameter documentation but lacks behavioral context and usage guidance. Without annotations or output schema, the agent doesn't know the return structure beyond 'List of invoices', which is insufficient for proper tool invocation and result interpretation.

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

Parameters5/5

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

The description adds substantial value beyond the input schema, which has 0% description coverage. It clearly explains all 5 parameters: their purposes, allowed values for 'status', date format for 'from_date' and 'to_date', and the default for 'limit'. This fully compensates for the schema's lack of descriptions and provides essential context for parameter usage.

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 with a specific verb ('List') and resource ('invoices'), and mentions optional filtering. It distinguishes from siblings like 'get_invoice' (singular) by indicating it returns multiple items. However, it doesn't explicitly differentiate from other list tools like 'list_clients' or 'list_attachments' beyond the resource type.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, compare with 'search_transactions' or 'get_invoice', or specify scenarios where filtering is beneficial. The agent must infer usage from the tool name and parameters alone.

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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