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felores

Airtable MCP Server

by felores

create_record

Add new records to Airtable tables by specifying base ID, table name, and field values to store structured data programmatically.

Instructions

Create a new record in a table

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
base_idYesID of the base
table_nameYesName of the table
fieldsYesRecord fields as key-value pairs

Implementation Reference

  • Handler for the create_record tool: extracts arguments, posts to Airtable API to create a record, and returns the response.
    case "create_record": {
      const { base_id, table_name, fields } = request.params.arguments as {
        base_id: string;
        table_name: string;
        fields: Record<string, any>;
      };
      const response = await this.axiosInstance.post(`/${base_id}/${table_name}`, {
        fields,
      });
      return {
        content: [{
          type: "text",
          text: JSON.stringify(response.data, null, 2),
        }],
      };
    }
  • src/index.ts:275-296 (registration)
    Registration of the create_record tool in the listTools response, including name, description, and input schema.
    {
      name: "create_record",
      description: "Create a new record in a table",
      inputSchema: {
        type: "object",
        properties: {
          base_id: {
            type: "string",
            description: "ID of the base",
          },
          table_name: {
            type: "string",
            description: "Name of the table",
          },
          fields: {
            type: "object",
            description: "Record fields as key-value pairs",
          },
        },
        required: ["base_id", "table_name", "fields"],
      },
    },
  • Input schema definition for the create_record tool, specifying parameters: base_id, table_name, and fields.
    inputSchema: {
      type: "object",
      properties: {
        base_id: {
          type: "string",
          description: "ID of the base",
        },
        table_name: {
          type: "string",
          description: "Name of the table",
        },
        fields: {
          type: "object",
          description: "Record fields as key-value pairs",
        },
      },
      required: ["base_id", "table_name", "fields"],
    },
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Create' implies a write/mutation operation, the description doesn't address permissions required, whether the operation is idempotent, what happens on conflicts, or what the response contains. For a mutation tool with zero annotation coverage, this leaves critical behavioral traits unspecified.

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 that states the core purpose without any fluff. It's front-loaded and wastes no words, making it easy to parse quickly. Every word earns its place in conveying the essential action.

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 complexity (a mutation tool with 3 required parameters, no annotations, and no output schema), the description is incomplete. It doesn't address behavioral aspects like side effects, error conditions, or return values, nor does it provide usage context relative to siblings. For a tool that creates database records, more guidance is needed to ensure correct invocation.

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 all three parameters (base_id, table_name, fields) with clear descriptions. The description adds no additional parameter semantics beyond what's in the schema—it doesn't explain format expectations, constraints, or examples. Baseline 3 is appropriate when the schema does the heavy lifting.

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 ('Create') and resource ('new record in a table'), making the purpose immediately understandable. It distinguishes from siblings like 'create_field' or 'create_table' by specifying 'record' rather than other database objects. However, it doesn't explicitly differentiate from 'update_record' in terms of creating vs. modifying existing records.

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. It doesn't mention prerequisites (e.g., needing an existing base and table), when to choose 'create_record' over 'update_record', or any constraints on usage. With multiple sibling tools available, this lack of contextual guidance is a significant gap.

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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