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Airtable MCP by InsightfulPipe

by com.insightfulpipe
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Airtable Data Execute Action

execute_action
Destructive

Execute Airtable action (Step 3 (FINAL) of workflow).

REQUIRED: Complete these steps first using query_contexts:

  1. request='accounts' - Get workspace_id, brand_id, gcp_project_id AND available_actions

  2. request='actions_details' with actions=['xxxxxx', 'xxxxxx', 'xxxxxx'] - Get detailed body structure for specific action(s) using actions from available_actions

IMPORTANT: Always call step 2 to see the exact body structure before executing.

Airtable is read-only here (OAuth scope airtable.readonly): only SELECT queries succeed; DDL/DML/scripts are rejected by Google.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "body": "<body>"
    },
    "name": "execute_action"
  }
}

Input Schema

NameRequiredDescriptionDefault
bodyYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior1/5

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

The description says Airtable is read-only here and only SELECT queries succeed, but annotations declare readOnlyHint=false and destructiveHint=true. That is a direct conflict about whether the tool can mutate or destroy data, so the behavioral disclosure is misleading despite adding OAuth scope details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the final-step purpose and then gives numbered prerequisites. It is mostly efficient, though the repeated emphasis on step 2 is slightly redundant.

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?

For a complex dynamic action tool, it explains the required upstream calls, the read-only restriction, and the OAuth scope, while an output schema exists for return values. The main completeness issue is the unresolved conflict with annotations rather than missing workflow guidance.

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?

The schema has 0% description coverage for the sole body parameter, so the description must compensate. It does so procedurally by requiring actions_details to reveal the exact body structure, but it does not describe the body fields itself.

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 states a specific verb and resource ("Execute Airtable action") and identifies it as Step 3, the FINAL step of a workflow. It distinguishes itself from query_contexts by making that tool a prerequisite rather than an alternative.

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

Usage Guidelines5/5

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

It gives explicit when-to-use prerequisites: call query_contexts with request='accounts' and then request='actions_details' before executing. It also states that only SELECT queries succeed and that DDL/DML/scripts are rejected, which tells the agent when not to use the tool.

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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