Skip to main content
Glama
felores

Airtable MCP Server

by felores

search_records

Find records in an Airtable table by searching a specific field for matching values to retrieve relevant data entries.

Instructions

Search for records in a table

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
base_idYesID of the base
table_nameYesName of the table
field_nameYesName of the field to search in
valueYesValue to search for

Implementation Reference

  • Handler function for the 'search_records' tool. Extracts parameters, makes an Airtable API GET request with a filterByFormula to match the specified field value, and returns the matching records as JSON.
    case "search_records": {
      const { base_id, table_name, field_name, value } = request.params.arguments as {
        base_id: string;
        table_name: string;
        field_name: string;
        value: string;
      };
      const response = await this.axiosInstance.get(`/${base_id}/${table_name}`, {
        params: {
          filterByFormula: `{${field_name}} = "${value}"`,
        },
      });
      return {
        content: [{
          type: "text",
          text: JSON.stringify(response.data.records, null, 2),
        }],
      };
    }
  • src/index.ts:346-370 (registration)
    Registration of the 'search_records' tool in the ListTools response, including its name, description, and input schema definition.
      name: "search_records",
      description: "Search for 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",
          },
          field_name: {
            type: "string",
            description: "Name of the field to search in",
          },
          value: {
            type: "string",
            description: "Value to search for",
          },
        },
        required: ["base_id", "table_name", "field_name", "value"],
      },
    },
  • Input schema definition for the 'search_records' tool, specifying required parameters: base_id, table_name, field_name, value.
      inputSchema: {
        type: "object",
        properties: {
          base_id: {
            type: "string",
            description: "ID of the base",
          },
          table_name: {
            type: "string",
            description: "Name of the table",
          },
          field_name: {
            type: "string",
            description: "Name of the field to search in",
          },
          value: {
            type: "string",
            description: "Value to search for",
          },
        },
        required: ["base_id", "table_name", "field_name", "value"],
      },
    },
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. It states the action ('search') but doesn't describe key behaviors: whether it returns all matches or is paginated, if the search is case-sensitive or supports wildcards, what happens on no matches (empty list or error), or any rate limits. This leaves significant gaps for a tool with 4 required parameters.

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 front-loads the core action ('search for records') and specifies the context ('in a table'), making it immediately clear. Every word earns its place, and there's no redundancy or fluff.

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 tool's complexity (4 required parameters, no output schema, and no annotations), the description is incomplete. It doesn't explain the return format (e.g., list of records, error handling), search behavior, or how to interpret results. Sibling tools suggest a rich context (e.g., CRUD operations on bases/tables/records), but this description lacks necessary details for 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 schema fully documents all 4 parameters (base_id, table_name, field_name, value). The description adds no additional semantic context beyond implying a search operation, such as how the value parameter is used (e.g., exact match, substring). This meets the baseline for high schema coverage but doesn't enhance understanding.

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 ('search') and resource ('records in a table'), making the purpose immediately understandable. It distinguishes itself from siblings like 'get_record' (singular retrieval) and 'list_records' (unfiltered listing). However, it doesn't specify the scope or type of search (e.g., exact match, partial, case-sensitive), which prevents 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?

The description provides no guidance on when to use this tool versus alternatives like 'list_records' (for unfiltered listing) or 'get_record' (for retrieving a specific record by ID). It also doesn't mention prerequisites, such as needing to know the base and table structure first, which could be inferred from sibling tools like 'list_bases' and 'list_tables'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/felores/airtable-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server