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felores

Airtable MCP Server

by felores

list_records

Retrieve records from an Airtable table by specifying the base ID and table name, with optional limit on results.

Instructions

List records in a table

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
base_idYesID of the base
table_nameYesName of the table
max_recordsNoMaximum number of records to return

Implementation Reference

  • The handler implementation for the 'list_records' tool. It destructures the input arguments, performs a GET request to the Airtable API to list records from the specified table (with optional maxRecords parameter), and returns the records as formatted JSON text content.
    case "list_records": {
      const { base_id, table_name, max_records } = request.params.arguments as {
        base_id: string;
        table_name: string;
        max_records?: number;
      };
      const response = await this.axiosInstance.get(`/${base_id}/${table_name}`, {
        params: max_records ? { maxRecords: max_records } : undefined,
      });
      return {
        content: [{
          type: "text",
          text: JSON.stringify(response.data.records, null, 2),
        }],
      };
    }
  • The input schema for the 'list_records' tool, defining the expected parameters: required base_id and table_name (strings), optional max_records (number). Used for validation in tool calls.
    inputSchema: {
      type: "object",
      properties: {
        base_id: {
          type: "string",
          description: "ID of the base",
        },
        table_name: {
          type: "string",
          description: "Name of the table",
        },
        max_records: {
          type: "number",
          description: "Maximum number of records to return",
        },
      },
      required: ["base_id", "table_name"],
    },
  • src/index.ts:253-274 (registration)
    The registration of the 'list_records' tool in the list of available tools returned by ListToolsRequestSchema. Includes name, description, and input schema.
    {
      name: "list_records",
      description: "List records 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",
          },
          max_records: {
            type: "number",
            description: "Maximum number of records to return",
          },
        },
        required: ["base_id", "table_name"],
      },
    },
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states the action but does not disclose pagination behavior, rate limits, permissions needed, or output format. This is inadequate for a read operation with potential complexity.

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 waste. It is front-loaded and appropriately sized for a simple tool, making it easy to parse 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?

Given no annotations, no output schema, and a read operation with potential behavioral nuances (e.g., pagination, ordering), the description is incomplete. It fails to address key contextual aspects like return format or limitations, leaving significant gaps for agent understanding.

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 documents all parameters (base_id, table_name, max_records). The description adds no additional meaning beyond implying a table context, matching the baseline for high schema coverage without extra param details.

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 'List records in a table' clearly states the action (list) and target resource (records in a table), distinguishing it from siblings like get_record (singular fetch) or search_records (filtered search). However, it lacks specificity about scope or format, keeping it from a perfect score.

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?

No guidance is provided on when to use this tool versus alternatives like search_records or get_record. The description implies a basic listing operation but does not specify use cases, prerequisites, or exclusions, leaving the agent to infer usage from context alone.

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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