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deyikong

SendGrid MCP Server

by deyikong

Create Custom Field

create_custom_field

Add custom fields to SendGrid contacts to store specific data like text, numbers, or dates for targeted email marketing and segmentation.

Instructions

Create a new custom field for contacts

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesName of the custom field
field_typeYesType of the field

Implementation Reference

  • The handler function that executes the tool logic: checks read-only mode and makes a POST request to SendGrid API to create the custom field.
    handler: async ({ name, field_type }: { name: string; field_type: string }): Promise<ToolResult> => {
      const readOnlyCheck = checkReadOnlyMode();
      if (readOnlyCheck.blocked) {
        return { content: [{ type: "text", text: readOnlyCheck.message! }] };
      }
      
      const result = await makeRequest("https://api.sendgrid.com/v3/marketing/field_definitions", {
        method: "POST",
        body: JSON.stringify({ name, field_type }),
      });
      return { content: [{ type: "text", text: JSON.stringify(result, null, 2) }] };
    },
  • Tool configuration with input schema using Zod for name (string) and field_type (enum: Text, Number, Date).
    config: {
      title: "Create Custom Field",
      description: "Create a new custom field for contacts",
      inputSchema: {
        name: z.string().describe("Name of the custom field"),
        field_type: z.enum(["Text", "Number", "Date"]).describe("Type of the field"),
      },
    },
  • The tool 'create_custom_field' is defined and registered within the contactTools object exported from this file.
    create_custom_field: {
      config: {
        title: "Create Custom Field",
        description: "Create a new custom field for contacts",
        inputSchema: {
          name: z.string().describe("Name of the custom field"),
          field_type: z.enum(["Text", "Number", "Date"]).describe("Type of the field"),
        },
      },
      handler: async ({ name, field_type }: { name: string; field_type: string }): Promise<ToolResult> => {
        const readOnlyCheck = checkReadOnlyMode();
        if (readOnlyCheck.blocked) {
          return { content: [{ type: "text", text: readOnlyCheck.message! }] };
        }
        
        const result = await makeRequest("https://api.sendgrid.com/v3/marketing/field_definitions", {
          method: "POST",
          body: JSON.stringify({ name, field_type }),
        });
        return { content: [{ type: "text", text: JSON.stringify(result, null, 2) }] };
      },
    },
  • contactTools (including create_custom_field) is merged into the allTools export used for MCP tool registration.
    ...contactTools,
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'Create' implies a write operation, it doesn't mention permission requirements, whether this action is reversible (see sibling 'delete_custom_field'), rate limits, or what happens on success/failure. The description lacks crucial behavioral context for a mutation tool.

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 appropriately sized for a simple creation tool and gets straight to the point without unnecessary elaboration.

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?

For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after creation, whether the field becomes immediately available, how to verify success, or potential constraints. Given the complexity of creating a system field and the lack of structured behavioral information, the description should provide more context.

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 already documents both parameters completely. The description adds no additional parameter information beyond what's in the schema. The baseline score of 3 reflects adequate but minimal value added by the description regarding parameters.

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 action ('Create') and resource ('new custom field for contacts'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'update_custom_field' or explain what distinguishes custom fields from other contact-related entities in the system.

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 like 'update_custom_field' or 'list_custom_fields'. It doesn't mention prerequisites, limitations, or typical use cases for creating custom fields versus using existing ones.

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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