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SmartSuiteFoundry

SmartSuite MCP Server

smartsuite_create_fields

Create multiple table fields in a single validated batch, with per-field success or error reporting so you can retry only the failed entries. Use this to avoid repeated single-field calls.

Instructions

Create MULTIPLE fields in one call — use this instead of calling smartsuite_create_field repeatedly. Requires readwrite/admin mode AND SMARTSUITE_ENABLE_SCHEMA_WRITE=true. Pass applicationId and fields: an array of { fieldType, label, params?, aiPrompt? } entries with exactly the same shape and semantics as smartsuite_create_field (see that tool for the per-type params guide). Slugs are generated. Every entry is validated before anything is written, so a malformed entry fails the whole call cleanly rather than half-creating the batch. Note SmartSuite has no bulk add-field API, so this performs one request per field (~1s each — a 20-field batch takes ~20s); it is sequential on purpose, because parallel field adds get rate-limited and silently drop fields. If a field fails, the batch continues and the result reports every field individually with created:true/false plus the error, so you can re-call with just the failures. Fields append to the end of the table in the order given (SmartSuite ignores field positioning on create — use smartsuite_move_layout_field to rearrange). TO CREATE A TABLE AND ITS FIELDS TOGETHER, pass fields to smartsuite_create_application instead — that provisions all of them in a SINGLE request and is far faster. Dry-run preview unless confirm:true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsYesThe fields to create, in order. Each entry: { fieldType, label, params?, aiPrompt? } — same semantics as smartsuite_create_field.
confirmNoMust be true to create (default false = preview).
applicationIdYesThe application (table) ID to add the fields to.

Schema Changelog

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

  1. Addedv1.0.0

TDQS

A4.9/5.0
Behavior5/5

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

With only readOnlyHint=false in annotations, the description carries the full behavioral burden and delivers thoroughly. It discloses that all entries are validated before writes, failed fields do not abort the batch, the call performs one request per field due to API limitations, sequential execution avoids rate limits and dropped fields, and fields append to the end of the table. This is rich, non-obvious behavior that annotations alone could never convey.

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 long but every clause earns its place: alternative routing, prerequisites, validation guarantees, performance expectations, failure semantics, ordering behavior, and an alternative batch path. Critical operational guidance is front-loaded, and no filler or tautological phrasing is present. The density is justified by the tool's complexity.

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

Completeness5/5

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

For a batch mutation tool with no output schema, this description is remarkably complete. It covers when to use it, prerequisites, validation behavior, performance characteristics, failure handling, result reporting format (created:true/false plus error), positioning semantics, a faster alternative, and the dry-run behavior. An agent has everything needed to invoke it correctly and recover from partial failures.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already documents all parameters at 100% coverage, so the baseline is 3. The description adds meaningful semantics beyond the schema: it specifies the exact entry shape, references smartsuite_create_field's per-type params guide for shared semantics, clarifies that slugs are generated, and explains order significance and failure-reporting implications. This goes beyond schema repetition without needing to document every fieldType-specific option.

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 opens with a specific verb and resource: 'Create MULTIPLE fields in one call.' It immediately distinguishes itself from the sibling smartsuite_create_field by framing it as the bulk alternative, so an agent knows exactly what this tool does and how it differs.

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?

The description explicitly tells the agent when to use this tool instead of repeatedly calling smartsuite_create_field, and when to use smartsuite_create_application instead for table-plus-fields creation. It also provides prerequisites (readwrite/admin mode, SMARTSUITE_ENABLE_SCHEMA_WRITE=true) and the confirm:true requirement, leaving no ambiguity about invocation conditions.

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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