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decode-data

twentycrm-graphql-mcp

by decode-data

inspect_schema

Inspect your Twenty CRM data model by listing all objects and fields, including custom fields, to enable precise GraphQL queries.

Instructions

Lists all available objects and fields, including CUSTOM fields created in your workspace.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observedv0.0.9

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations provided, the description carries the full disclosure burden. It clearly signals a read-only listing operation through the verb 'lists' and adds useful nuance by highlighting that custom fields created in the workspace are included. There is no hidden mutation or side-effect behavior implied.

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, front-loaded sentence that states the core behavior first and then adds the key detail about custom fields. Every word earns its place, with no fluff or repetition.

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 zero-parameter introspection tool, the description is largely complete: it identifies the operation, the resource, and a notable scope detail. It does not describe the output shape, but the absence of an output schema and the low complexity make this a minor gap rather than a serious omission.

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 has zero parameters, so there are no parameter semantics to compensate for. The baseline for zero-parameter tools is 4, and the description does not need to explain anything about parameters.

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: it lists all available objects and fields, and explicitly calls out custom fields in the workspace. This makes the tool's purpose clear, though it does not explicitly distinguish itself from its siblings beyond the verb 'lists' versus their 'execute' naming.

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 that the tool should be used when you need to discover available schema objects and fields, including custom ones. However, it gives no explicit guidance on when to prefer this tool over execute_graphql or execute_metadata, nor any exclusions or alternatives.

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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