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Glama

Airtable

by io.github.pipeworx-io

Airtable Get Record

airtable_get_record
Read-onlyIdempotent

Fetch a single Airtable record by its record ID (recXXXXXXXXXXXX) from a specified base and table. Returns all field values and record metadata including created/modified timestamps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
baseIdYesAirtable base ID
_apiKeyYesAirtable personal access token
recordIdYesRecord ID (e.g., recXXXXXXXXXXXX)
tableIdOrNameYesTable ID or name

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesRecord ID
fieldsYesAll field name/value pairs for this record
createdTimeYesISO timestamp when record was created

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "createdTime": {
+      "description": "ISO timestamp when record was created",
+      "type": "string"
+    },
+    "fields": {
+      "description": "All field name/value pairs for this record",
+      "type": "object"
+    },
+    "id": {
+      "description": "Record ID",
+      "type": "string"
+    }
+  },
+  "required": [
+    "id",
+    "fields",
+    "createdTime"
+  ],
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "_apiKey": "your-airtable-api-key",
+    "baseId": "appXXXXXXXXXXXX",
+    "recordId": "recXXXXXXXXXXXX",
+    "tableIdOrName": "Tasks"
+  }
+]
  3. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive nature. The description adds useful detail about return values (all field values and metadata like timestamps), which goes beyond the annotations without contradicting them.

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?

Two sentences that are front-loaded with the action and inputs, followed by output details. No redundant information or unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given an output schema exists, the description appropriately focuses on the tool's purpose and key inputs. It covers the essential aspects (base, table, record ID, returns fields and metadata) without missing critical details. Could mention error handling but not required.

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 description adds minimal new information beyond the schema. It mentions the record ID format (recXXXXXXXXXXXX) but does not explain other parameters. Baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Fetch', the resource 'a single Airtable record', and specifies the key identifiers (record ID, base, table). It distinguishes from siblings like airtable_list_records (which retrieves multiple records) and airtable_create_record.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when you have a specific record ID, but does not explicitly state when to use this tool versus alternatives (e.g., listing records with airtable_list_records). No direct comparison or exclusions are provided.

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

All Airtable toolsInspect
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TDQS

A3.5/5.0
Disambiguation2/5

The Airtable tools are distinct, but the set is dominated by a large Pipeworx research family with multiple near-identical entries (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and several overlapping prediction-market tools (bet_research, polymarket_edges, polymarket_arbitrage). An agent would frequently struggle to pick the right tool among the many data-lookup and research options, especially given the server is supposedly named Airtable.

Naming Consistency2/5

Naming conventions are mixed: some tools use verb_noun snake_case (airtable_create_record, list_subscriptions, resolve_entity), while others use domain-prefixed names (pipeworx_feedback, polymarket_edges) or bare verbs (remember, forget, recall, subscribe). There is no single predictable pattern across the set.

Tool Count2/5

36 tools is heavy for any single server's scope, and the mismatch is worse because the server is named Airtable yet only 5 of 36 tools relate to Airtable. The rest form an unrelated Pipeworx/Polymarket/memory grab-bag, suggesting poor scoping and no clear purpose for the set as a whole.

Completeness2/5

For the stated Airtable domain, the surface is incomplete: records can be created, fetched, and listed, but there is no update_record or delete_record. For the broader Pipeworx/prediction-market domain the coverage is extensive but unfocused, and given the server's name the Airtable gap is glaring.

Resources