Skip to main content
Glama

get_documents

Retrieve ERPNext documents by doctype with optional filters, fields selection, and result limits for data management.

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

  • Handler for the 'get_documents' tool call. Extracts parameters, validates doctype, calls erpnext.getDocList, and returns the JSON list or error.
    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
        };
      }
    }
  • src/index.ts:349-378 (registration)
    Registration of the 'get_documents' tool in listTools response, including name, description, and input schema.
    {
      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"]
      }
    },
  • Input schema definition for the 'get_documents' tool, specifying parameters like doctype, fields, filters, and limit.
    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"]
    }
  • Core helper function getDocList in ERPNextClient class that performs the API call to fetch documents list based on doctype, filters, fields, and limit.
    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'}`);
      }
    }

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior2/5

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

With no annotations, the description carries the full burden for behavioral disclosure. It only states a basic listing operation and does not mention read-only nature, pagination, sorting, return format, or any side effects. The agent cannot predict behavior beyond the name.

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, front-loaded sentence that is efficient and free of unnecessary words. It communicates the core purpose without redundancy.

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 the tool has 4 parameters, a nested filters object, no output schema, and no annotations, the description is too sparse. It does not explain list behavior, filtering interplay, pagination, or return structure, leaving the agent under-informed for a tool of this complexity.

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 itself documents all parameters adequately. The description adds no extra meaning beyond the schema (e.g., 'for a specific doctype' merely restates the doctype parameter). Baseline 3 is appropriate.

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 uses a specific verb ('Get') and resource ('a list of documents') with a clear qualifier ('for a specific doctype'). This directly contrasts with sibling tools like get_doctypes and get_doctype_fields, making the tool's purpose unambiguous.

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

Usage Guidelines4/5

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

The phrase 'for a specific doctype' implies usage context and helps distinguish from sibling tools, but there is no explicit when-to-use or when-not-to-use guidance. It is clear enough for an agent to select this tool over alternatives, but lacks explicit exclusions.

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