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list_collections

Read-onlyIdempotent

Retrieve prompt collections filtered by name or workspace. Returns collection IDs, names, slugs, and timestamps for selecting a collection before creating prompts.

Instructions

List prompt collections in the workspace, optionally filtering by name or workspace. Returns ids, names, slugs, and timestamps so you can choose a collection_id before create_prompt, get_collection, or list_prompts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspace_idNoFilter by workspace ID
searchNoSearch collections by name
current_pageNoPage number for pagination
page_sizeNoResults per page (max 100)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYesWhether the tool call succeeded and returned structured data
dataNoStructured success payload when ok is true
errorNoStructured error payload when ok is false

Implementation Reference

  • The MCP tool handler for 'list_collections'. It calls service.collections.listCollections(params) and returns the total and mapped collection data (id, name, slug, workspace_id, created_at, last_updated_at) as JSON.
    server.tool(
    	"list_collections",
    	"List prompt collections in the workspace, optionally filtering by name or workspace. Returns ids, names, slugs, and timestamps so you can choose a collection_id before create_prompt, get_collection, or list_prompts.",
    	COLLECTIONS_TOOL_SCHEMAS.listCollections,
    	async (params) => {
    		const collections = await service.collections.listCollections(params);
    		return {
    			content: [
    				{
    					type: "text",
    					text: JSON.stringify(
    						{
    							total: collections.total,
    							collections: collections.data.map((collection) => ({
    								id: collection.id,
    								name: collection.name,
    								slug: collection.slug,
    								workspace_id: collection.workspace_id,
    								created_at: collection.created_at,
    								last_updated_at: collection.last_updated_at,
    							})),
    						},
    						null,
    						2,
    					),
    				},
    			],
    		};
    	},
    );
  • Zod schema for list_collections input params: optional workspace_id, search, current_page (positive int), page_size (1-100).
    listCollections: {
    	workspace_id: z.string().optional().describe("Filter by workspace ID"),
    	search: z.string().optional().describe("Search collections by name"),
    	current_page: z.coerce
    		.number()
    		.positive()
    		.optional()
    		.describe("Page number for pagination"),
    	page_size: z.coerce
    		.number()
    		.positive()
    		.max(100)
    		.optional()
    		.describe("Results per page (max 100)"),
    },
  • Registration of the 'list_collections' tool via server.tool() with name, description, schema, and handler callback.
    export function registerCollectionsTools(
    	server: McpServer,
    	service: PortkeyService,
    ): void {
    	// List collections tool
    	server.tool(
    		"list_collections",
    		"List prompt collections in the workspace, optionally filtering by name or workspace. Returns ids, names, slugs, and timestamps so you can choose a collection_id before create_prompt, get_collection, or list_prompts.",
    		COLLECTIONS_TOOL_SCHEMAS.listCollections,
    		async (params) => {
    			const collections = await service.collections.listCollections(params);
    			return {
    				content: [
    					{
    						type: "text",
    						text: JSON.stringify(
    							{
    								total: collections.total,
    								collections: collections.data.map((collection) => ({
    									id: collection.id,
    									name: collection.name,
    									slug: collection.slug,
    									workspace_id: collection.workspace_id,
    									created_at: collection.created_at,
    									last_updated_at: collection.last_updated_at,
    								})),
    							},
    							null,
    							2,
    						),
    					},
    				],
    			};
    		},
    	);
  • Service method CollectionsService.listCollections() that calls the HTTP API GET /collections with optional query params.
    async listCollections(
    	params?: ListCollectionsParams,
    ): Promise<ListCollectionsResponse> {
    	return this.get<ListCollectionsResponse>("/collections", {
    		workspace_id: params?.workspace_id,
    		current_page: params?.current_page,
    		page_size: params?.page_size,
    		search: params?.search,
    	});
    }
  • TypeScript interfaces ListCollectionsParams and ListCollectionsResponse used by the list_collections handler and service.
    export interface ListCollectionsParams {
    	workspace_id?: string;
    	current_page?: number;
    	page_size?: number;
    	search?: string;
    }
    
    export interface ListCollectionsResponse {
    	data: Collection[];
    	total: number;
    	object: "list";
    }
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true. The description adds value by specifying the return fields (ids, names, slugs, timestamps) and the optional filtering behavior. No contradictions with annotations.

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?

Two concise sentences, front-loaded with the primary action and followed by return values and usage context. Every sentence adds value without redundancy.

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?

Given the presence of an output schema and comprehensive annotations, the description is complete. It mentions the primary return fields and the intended usage context, aligning well with the tool's simplicity and the structured metadata.

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 four parameters. The description's mention of filtering by name or workspace merely restates schema information without adding new semantics, meeting the baseline but not exceeding it.

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 the tool's purpose: listing prompt collections in the workspace, with optional filtering by name or workspace. It distinguishes from sibling tools by specifying the resource type and mentioning downstream tools like create_prompt, get_collection, and list_prompts.

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 provides clear usage context by stating the tool is useful for obtaining a collection_id before using create_prompt, get_collection, or list_prompts. It does not explicitly exclude use cases or mention alternatives, but the guidance is sufficient for typical scenarios.

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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