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jdlar1

Siigo MCP Server

by jdlar1

siigo_get_vouchers

Retrieve cash receipt vouchers from Siigo accounting software for financial tracking and record management.

Instructions

Get list of vouchers (cash receipts) from Siigo

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number
page_sizeNoNumber of items per page

Implementation Reference

  • src/index.ts:481-491 (registration)
    Tool registration in getTools() method, defining the tool name, description, and input schema for pagination.
    {
      name: 'siigo_get_vouchers',
      description: 'Get list of vouchers (cash receipts) from Siigo',
      inputSchema: {
        type: 'object',
        properties: {
          page: { type: 'number', description: 'Page number' },
          page_size: { type: 'number', description: 'Number of items per page' },
        },
      },
    },
  • MCP server handler that invokes the SiigoClient.getVouchers and formats the response.
    private async handleGetVouchers(args: any) {
      const result = await this.siigoClient.getVouchers(args);
      return { content: [{ type: 'text', text: JSON.stringify(result, null, 2) }] };
  • Dispatch case in the main switch statement for routing tool calls to the handler.
    case 'siigo_get_vouchers':
      return await this.handleGetVouchers(args);
  • Core handler in SiigoClient that performs the authenticated GET request to Siigo API endpoint /v1/vouchers with optional pagination parameters.
    async getVouchers(params?: { page?: number; page_size?: number }): Promise<SiigoApiResponse<any>> {
      return this.makeRequest<any>('GET', '/v1/vouchers', undefined, params);
    }
  • Helper method used by all API calls, handling authentication, HTTP requests via Axios, and error handling.
    private async makeRequest<T>(method: string, endpoint: string, data?: any, params?: any): Promise<SiigoApiResponse<T>> {
      await this.authenticate();
    
      try {
        const response: AxiosResponse<SiigoApiResponse<T>> = await this.httpClient.request({
          method,
          url: endpoint,
          data,
          params,
        });
    
        return response.data;
      } catch (error: any) {
        if (error.response?.data) {
          return error.response.data;
        }
        throw new Error(`API request failed: ${error.message}`);
      }
    }
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It implies a read-only operation ('Get list') but doesn't disclose critical traits like pagination behavior (implied by parameters but not explained), rate limits, authentication needs, or error handling. This is inadequate for a tool with parameters.

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 a single, efficient sentence with zero wasted words. It's front-loaded with the core action ('Get list of vouchers') and includes clarifying parenthetical information ('cash receipts'), making it highly concise and well-structured.

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

Completeness2/5

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

Given no annotations, no output schema, and a read operation with parameters, the description is incomplete. It fails to explain behavioral aspects like pagination, return format, or error conditions, leaving significant gaps for an AI agent to understand tool usage effectively.

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 parameters 'page' and 'page_size' are documented in the schema. The description adds no additional meaning beyond implying list retrieval, which the schema already supports. Baseline 3 is appropriate as the schema handles parameter documentation.

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 verb ('Get') and resource ('list of vouchers (cash receipts) from Siigo'), making the purpose unambiguous. However, it doesn't differentiate from its sibling 'siigo_get_voucher' (singular), which likely retrieves a single voucher, leaving some ambiguity about scope.

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?

No guidance is provided on when to use this tool versus alternatives like 'siigo_get_voucher' or other list-retrieval tools (e.g., 'siigo_get_invoices'). The description lacks context about prerequisites, such as authentication or data availability, leaving usage unclear.

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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