Retrieve organization field definitions, including custom fields, to convert 40-character keys into readable names.
List all organization field definitions, including custom fields. Use this to map 40-character field keys to human-readable names.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of items (1-100) | |
| cursor | No | Cursor for pagination (from previous response) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
v2.4.0Input schema / properties / cursorAdded value: +{
+ "description": "Cursor for pagination (from previous response)",
+ "type": "string"
+}Input schema / properties / limit / descriptionPrevious value: -"Number of items"New value: +"Number of items (1-100)"Input schema / properties / startRemoved value: -{
- "description": "Pagination offset",
- "type": "number"
-}v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint, openWorldHint. The description adds value by specifying inclusive scope (all fields, including custom) and the mapping purpose, enhancing transparency about what the tool returns.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with key info, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description hints at output as field definitions with key-name mapping. Adequate for a listing tool with good annotations; could clarify structure slightly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for cursor and limit. Description does not add new parameter details beyond schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it lists all organization field definitions including custom fields, and adds a practical use case of mapping field keys to human-readable names. Distinct from sibling tools like pipedrive_list_organizations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies when to use: when needing to map field keys to names. Context is clear given sibling tools are for different purposes; could explicitly mention alternatives like pipedrive_get_field.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/ckalima/pipedrive-mcp-server'
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