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get_documents

Retrieve ERPNext documents by DocType using optional filters, fields, and limits to access specific business records.

Instructions

Get a list of documents for a specific doctype

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
doctypeYesERPNext DocType (e.g., Customer, Item)
fieldsNoFields to include (optional)
filtersNoFilters in the format {field: value} (optional)
limitNoMaximum number of documents to return (optional)

Implementation Reference

  • Main handler for 'get_documents' tool. Validates authentication, extracts parameters (doctype, fields, filters, limit), calls erpnext.getDocList(), and returns formatted results or error messages.
    case "get_documents": {
      if (!erpnext.isAuthenticated()) {
        return {
          content: [{
            type: "text",
            text: "Not authenticated with ERPNext. Please configure API key authentication."
          }],
          isError: true
        };
      }
      
      const doctype = String(request.params.arguments?.doctype);
      const fields = request.params.arguments?.fields as string[] | undefined;
      const filters = request.params.arguments?.filters as Record<string, any> | undefined;
      const limit = request.params.arguments?.limit as number | undefined;
      
      if (!doctype) {
        throw new McpError(
          ErrorCode.InvalidParams,
          "Doctype is required"
        );
      }
      
      try {
        const documents = await erpnext.getDocList(doctype, filters, fields, limit);
        return {
          content: [{
            type: "text",
            text: JSON.stringify(documents, null, 2)
          }]
        };
      } catch (error: any) {
        return {
          content: [{
            type: "text",
            text: `Failed to get ${doctype} documents: ${error?.message || 'Unknown error'}`
          }],
          isError: true
        };
      }
    }
  • Input schema definition for 'get_documents' tool. Defines the JSON schema for tool input validation with properties: doctype (required string), fields (optional string array), filters (optional object), and limit (optional number).
    {
      name: "get_documents",
      description: "Get a list of documents for a specific doctype",
      inputSchema: {
        type: "object",
        properties: {
          doctype: {
            type: "string",
            description: "ERPNext DocType (e.g., Customer, Item)"
          },
          fields: {
            type: "array",
            items: {
              type: "string"
            },
            description: "Fields to include (optional)"
          },
          filters: {
            type: "object",
            additionalProperties: true,
            description: "Filters in the format {field: value} (optional)"
          },
          limit: {
            type: "number",
            description: "Maximum number of documents to return (optional)"
          }
        },
        required: ["doctype"]
      }
    },
  • ERPNextClient.getDocList() method - the core helper that makes the actual HTTP API call to ERPNext. Builds query parameters from fields, filters, and limit, then performs a GET request to /api/resource/{doctype} and returns the document list.
    async getDocList(doctype: string, filters?: Record<string, any>, fields?: string[], limit?: number): Promise<any[]> {
      try {
        let params: Record<string, any> = {};
        
        if (fields && fields.length) {
          params['fields'] = JSON.stringify(fields);
        }
        
        if (filters) {
          params['filters'] = JSON.stringify(filters);
        }
        
        if (limit) {
          params['limit_page_length'] = limit;
        }
        
        const response = await this.axiosInstance.get(`/api/resource/${doctype}`, { params });
        return response.data.data;
      } catch (error: any) {
        throw new Error(`Failed to get ${doctype} list: ${error?.message || 'Unknown error'}`);
      }
    }
Behavior2/5

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

Lacks annotations and description omits read-only nature, pagination behavior with limit parameter, or filter matching logic.

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

Conciseness3/5

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

Single sentence is concise but undersized for tool complexity (4 parameters including nested filter objects); front-loading is moot given brevity.

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?

Missing return value structure given no output schema, and omits query behavior details (e.g., filter wildcard support) necessary for effective use.

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 has 100% description coverage meeting baseline; main description adds no parameter context but none is required given comprehensive schema.

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

Purpose2/5

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

Tautological restatement of tool name ('Get a list of documents') with minimal addition; fails to distinguish from siblings like get_doctypes or run_report.

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?

Provides no guidance on when to use this versus alternatives like run_report for complex queries or get_doctype_fields for metadata.

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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