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felores

Airtable MCP Server

by felores

update_record

Modify existing records in Airtable tables by specifying base ID, table name, record ID, and field updates to change stored data programmatically.

Instructions

Update an existing record in a table

Input Schema

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

Implementation Reference

  • Handler implementation for the update_record tool. Extracts arguments from the request and performs a PATCH request to the Airtable API to update the specified record.
    case "update_record": {
      const { base_id, table_name, record_id, fields } = request.params.arguments as {
        base_id: string;
        table_name: string;
        record_id: string;
        fields: Record<string, any>;
      };
      const response = await this.axiosInstance.patch(
        `/${base_id}/${table_name}/${record_id}`,
        { fields }
      );
      return {
        content: [{
          type: "text",
          text: JSON.stringify(response.data, null, 2),
        }],
      };
    }
  • src/index.ts:297-322 (registration)
    Registration of the update_record tool, including its name, description, and input schema definition.
    {
      name: "update_record",
      description: "Update an existing 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",
          },
          record_id: {
            type: "string",
            description: "ID of the record to update",
          },
          fields: {
            type: "object",
            description: "Record fields to update as key-value pairs",
          },
        },
        required: ["base_id", "table_name", "record_id", "fields"],
      },
    },
  • Input schema definition for the update_record tool, specifying parameters like base_id, table_name, record_id, and fields.
    inputSchema: {
      type: "object",
      properties: {
        base_id: {
          type: "string",
          description: "ID of the base",
        },
        table_name: {
          type: "string",
          description: "Name of the table",
        },
        record_id: {
          type: "string",
          description: "ID of the record to update",
        },
        fields: {
          type: "object",
          description: "Record fields to update as key-value pairs",
        },
      },
      required: ["base_id", "table_name", "record_id", "fields"],
    },
Behavior2/5

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 implies a mutation operation but doesn't cover critical aspects like required permissions, whether updates are reversible, error handling for invalid inputs, or rate limits. This leaves significant gaps for a tool that modifies data.

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 no wasted words, clearly front-loading the core purpose. It's appropriately sized for a straightforward tool, making it easy to parse quickly.

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 of a mutation tool with no annotations and no output schema, the description is insufficient. It lacks details on behavioral traits, error conditions, or what the tool returns, leaving the agent with incomplete context for safe and effective use.

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 input schema fully documents all four parameters (base_id, table_name, record_id, fields). The description adds no additional meaning beyond what's in the schema, such as explaining the structure of 'fields' or providing examples, which aligns with the baseline score when schema coverage is high.

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 ('Update') and target ('an existing record in a table'), which is specific and distinguishes it from siblings like create_record or delete_record. However, it doesn't specify what kind of updates are possible (e.g., field modifications) beyond the basic verb+resource.

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 update_field or update_table, nor does it mention prerequisites such as needing an existing record ID. The description only states what it does, not when or why to choose it.

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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