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salesforce_dml_records

Insert, update, delete, or upsert records in Salesforce objects to manage data operations through the Salesforce MCP Server.

Instructions

Perform data manipulation operations on Salesforce records:

  • insert: Create new records

  • update: Modify existing records (requires Id)

  • delete: Remove records (requires Id)

  • upsert: Insert or update based on external ID field Examples: Insert new Accounts, Update Case status, Delete old records, Upsert based on custom external ID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
operationYesType of DML operation to perform
objectNameYesAPI name of the object
recordsYesArray of records to process
externalIdFieldNoExternal ID field name for upsert operations

Implementation Reference

  • Core handler function that performs Salesforce DML operations (insert, update, delete, upsert) based on input arguments, handles results and errors, and returns formatted text response.
    export async function handleDMLRecords(conn: any, args: DMLArgs) {
      const { operation, objectName, records, externalIdField } = args;
    
      let result: DMLResult | DMLResult[];
      
      switch (operation) {
        case 'insert':
          result = await conn.sobject(objectName).create(records);
          break;
        case 'update':
          result = await conn.sobject(objectName).update(records);
          break;
        case 'delete':
          result = await conn.sobject(objectName).destroy(records.map(r => r.Id));
          break;
        case 'upsert':
          if (!externalIdField) {
            throw new Error('externalIdField is required for upsert operations');
          }
          result = await conn.sobject(objectName).upsert(records, externalIdField);
          break;
        default:
          throw new Error(`Unsupported operation: ${operation}`);
      }
    
      // Format DML results
      const results = Array.isArray(result) ? result : [result];
      const successCount = results.filter(r => r.success).length;
      const failureCount = results.length - successCount;
    
      let responseText = `${operation.toUpperCase()} operation completed.\n`;
      responseText += `Processed ${results.length} records:\n`;
      responseText += `- Successful: ${successCount}\n`;
      responseText += `- Failed: ${failureCount}\n\n`;
    
      if (failureCount > 0) {
        responseText += 'Errors:\n';
        results.forEach((r: DMLResult, idx: number) => {
          if (!r.success && r.errors) {
            responseText += `Record ${idx + 1}:\n`;
            if (Array.isArray(r.errors)) {
              r.errors.forEach((error) => {
                responseText += `  - ${error.message}`;
                if (error.statusCode) {
                  responseText += ` [${error.statusCode}]`;
                }
                if (error.fields && error.fields.length > 0) {
                  responseText += `\n    Fields: ${error.fields.join(', ')}`;
                }
                responseText += '\n';
              });
            } else {
              // Single error object
              const error = r.errors;
              responseText += `  - ${error.message}`;
              if (error.statusCode) {
                responseText += ` [${error.statusCode}]`;
              }
              if (error.fields) {
                const fields = Array.isArray(error.fields) ? error.fields.join(', ') : error.fields;
                responseText += `\n    Fields: ${fields}`;
              }
              responseText += '\n';
            }
          }
        });
      }
    
      return {
        content: [{
          type: "text",
          text: responseText
        }],
        isError: false,
      };
    }
  • Tool definition including name, description, and JSON input schema for validating arguments to the salesforce_dml_records tool.
    export const DML_RECORDS: Tool = {
      name: "salesforce_dml_records",
      description: `Perform data manipulation operations on Salesforce records:
      - insert: Create new records
      - update: Modify existing records (requires Id)
      - delete: Remove records (requires Id)
      - upsert: Insert or update based on external ID field
      Examples: Insert new Accounts, Update Case status, Delete old records, Upsert based on custom external ID`,
      inputSchema: {
        type: "object",
        properties: {
          operation: {
            type: "string",
            enum: ["insert", "update", "delete", "upsert"],
            description: "Type of DML operation to perform"
          },
          objectName: {
            type: "string",
            description: "API name of the object"
          },
          records: {
            type: "array",
            items: { type: "object" },
            description: "Array of records to process"
          },
          externalIdField: {
            type: "string",
            description: "External ID field name for upsert operations",
            optional: true
          }
        },
        required: ["operation", "objectName", "records"]
      }
    };
  • src/tools/dml.ts:83-95 (registration)
    Tool handler registration in the main CallToolRequest switch statement: validates input arguments, casts to DMLArgs type, and invokes the handleDMLRecords function.
    results.forEach((r: DMLResult, idx: number) => {
      if (!r.success && r.errors) {
        responseText += `Record ${idx + 1}:\n`;
        if (Array.isArray(r.errors)) {
          r.errors.forEach((error) => {
            responseText += `  - ${error.message}`;
            if (error.statusCode) {
              responseText += ` [${error.statusCode}]`;
            }
            if (error.fields && error.fields.length > 0) {
              responseText += `\n    Fields: ${error.fields.join(', ')}`;
            }
            responseText += '\n';
  • src/index.ts:35-44 (registration)
    Registration of the tool in the ListToolsRequest handler by including DML_RECORDS in the exported tools list.
    server.setRequestHandler(ListToolsRequestSchema, async () => ({
      tools: [
        SEARCH_OBJECTS, 
        DESCRIBE_OBJECT, 
        QUERY_RECORDS, 
        DML_RECORDS,
        MANAGE_OBJECT,
        MANAGE_FIELD,
        SEARCH_ALL
      ],
Behavior3/5

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 correctly identifies this as a data manipulation tool with destructive operations (delete) and mutation operations (insert, update, upsert). However, it lacks critical behavioral details like permission requirements, transaction boundaries, error handling, or rate limits that would be important for an agent to use this tool safely.

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 clear opening statement followed by bullet points for operation types and specific examples. Every sentence adds value, with no redundant information. The bullet format makes it easy to scan and understand quickly.

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?

For a complex DML tool with no annotations and no output schema, the description provides adequate basic information about operations but lacks important context. Missing elements include: expected return format, error behavior, permission requirements, and transactional guarantees. The examples help but don't fully compensate for the lack of structured behavioral metadata.

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

Parameters4/5

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

Schema description coverage is 100%, so the schema already documents all parameters well. The description adds meaningful context by explaining what each operation type does and providing concrete examples that help interpret the 'records' parameter content. However, it doesn't fully explain the structure of records objects or externalIdField usage beyond mentioning it's for upsert.

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 performs 'data manipulation operations on Salesforce records' and lists specific operations (insert, update, delete, upsert) with brief explanations. It distinguishes from sibling tools like salesforce_query_records (read-only) and salesforce_describe_object (metadata) by focusing on write operations.

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 description provides clear context for when to use each operation type (e.g., 'update: Modify existing records (requires Id)') and includes examples. However, it doesn't explicitly state when NOT to use this tool versus alternatives like salesforce_manage_object for object-level operations or provide prerequisites beyond ID requirements.

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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