Skip to main content
Glama

fields_search_fields

Search for fields by name or key across entity types like deals, persons, and organizations to find custom field definitions and metadata.

Instructions

Search for fields by name or key across entity types.

Searches field definitions by matching against field names (case-insensitive) or field keys. Useful for finding specific custom fields when you don't know the exact field ID.

Search is performed across:

  • Field names (e.g., "Customer Type", "Lead Source")

  • Field keys (e.g., "9dc80c50d78a...")

Results include:

  • Entity type the field belongs to

  • Field ID, key, and name

  • Field type and validation info

  • All other field metadata

Cached for 15 minutes as field definitions rarely change.

Common use cases:

  • Find field by name: { "query": "customer" }

  • Find field by partial key: { "query": "9dc80c" }

  • Search in specific entity: { "query": "status", "entity_type": "deal" }

  • Find all custom fields containing "date"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query to match against field names or keys
entity_typeNoOptional: Limit search to specific entity type. Default: "all"
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses caching behavior (15 minutes) and search scope across names and keys. Could mention response pagination or limits for completeness.

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 well-structured with bullet points for scope, results, and common uses. It is concise yet comprehensive, earning its sentences without redundancy.

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 no output schema, the description explains result fields (entity type, ID, key, name, type, validation). It could mention whether results are paginated or limited, but overall is sufficient for a search tool.

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?

Schema covers all parameters with descriptions. The description adds value by providing example queries and explaining partial key matching, which enhances understanding beyond the schema.

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 'Search for fields by name or key across entity types.' It uses specific verbs and resources, distinguishing itself from sibling tools like fields_list_all_fields and search_by_field.

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

Usage Guidelines4/5

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

The description includes common use cases and examples, such as finding a field by name or searching in a specific entity. However, it does not explicitly state when to avoid this tool or suggest alternatives.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/iamsamuelfraga/mcp-pipedrive'

If you have feedback or need assistance with the MCP directory API, please join our Discord server