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LawrenceCirillo

QuickBase MCP Server

quickbase_create_lookup_field

Create a lookup field in QuickBase to pull data from a related table by specifying parent and child table IDs, field references, and a label for the new field.

Instructions

Create a lookup field to pull data from a related table

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
childTableIdYesChild table ID where lookup field will be created
lookupFieldLabelYesLabel for the new lookup field
parentFieldIdYesField ID in parent table to lookup
parentTableIdYesParent table ID to lookup from
referenceFieldIdYesReference field ID in child table

Implementation Reference

  • Core handler function that executes the QuickBase API call to create a lookup field using the specified reference and lookup parameters.
    async createLookupField(
      childTableId: string,
      parentTableId: string,
      referenceFieldId: number,
      parentFieldId: number,
      lookupFieldLabel: string
    ): Promise<number> {
      const response = await this.axios.post('/fields', {
        tableId: childTableId,
        label: lookupFieldLabel,
        fieldType: 'lookup',
        properties: {
          lookupReference: {
            tableId: parentTableId,
            fieldId: parentFieldId,
            referenceFieldId: referenceFieldId
          }
        }
      });
      return response.data.id;
    }
  • Zod schema defining the input validation for the tool's parameters.
    const CreateLookupFieldSchema = z.object({
      childTableId: z.string().describe('Child table ID where lookup field will be created'),
      parentTableId: z.string().describe('Parent table ID to lookup from'),
      referenceFieldId: z.number().describe('Reference field ID in child table'),
      parentFieldId: z.number().describe('Field ID in parent table to lookup'),
      lookupFieldLabel: z.string().describe('Label for the new lookup field')
    });
  • MCP tool registration object defining the tool's metadata and input schema for use in the server.
      name: 'quickbase_create_lookup_field',
      description: 'Create a lookup field to pull data from a related table',
      inputSchema: {
        type: 'object',
        properties: {
          childTableId: { type: 'string', description: 'Child table ID where lookup field will be created' },
          parentTableId: { type: 'string', description: 'Parent table ID to lookup from' },
          referenceFieldId: { type: 'number', description: 'Reference field ID in child table' },
          parentFieldId: { type: 'number', description: 'Field ID in parent table to lookup' },
          lookupFieldLabel: { type: 'string', description: 'Label for the new lookup field' }
        },
        required: ['childTableId', 'parentTableId', 'referenceFieldId', 'parentFieldId', 'lookupFieldLabel']
      }
    },
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. It states 'Create a lookup field,' implying a write/mutation operation, but doesn't disclose behavioral traits like required permissions, whether it's idempotent, error handling, or what happens on success/failure. This is a significant gap for a mutation tool with zero annotation coverage.

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 that directly states the tool's purpose without any fluff or redundancy. It's appropriately sized and front-loaded, making it easy to understand at a glance.

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?

For a mutation tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It lacks behavioral context (e.g., permissions, side effects), usage guidelines, and any details on return values or errors, making it inadequate for safe and effective use by an AI agent.

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 already documents all 5 parameters with clear descriptions. The description adds no additional meaning beyond the schema, such as explaining relationships between parameters or usage examples. Baseline 3 is appropriate when the schema does the heavy lifting.

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 action ('Create a lookup field') and the resource ('to pull data from a related table'), which is specific and unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'quickbase_create_field' or 'quickbase_create_relationship', which might also create fields or relationships, so it misses full sibling distinction.

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, such as 'quickbase_create_field' for general field creation or 'quickbase_create_relationship' for other relationship types. There's no mention of prerequisites, context, or exclusions, leaving usage unclear.

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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