sort_by_relevance

Sort documents by their relevance to a specific query using Jina AI's reranking technology. Organize search results or content collections to prioritize information that best matches your topic.

Instructions

Rerank a list of documents by relevance to a query using Jina Reranker API. Use this when you have multiple documents and want to sort them by how well they match a specific query or topic. Perfect for document retrieval, content filtering, or finding the most relevant information from a collection.

Input Schema

TableJSON Schema

Name	Required	Description
`query`	Yes	The query or topic to rank documents against (e.g., 'machine learning algorithms', 'climate change solutions')
`documents`	Yes	Array of document texts to rerank by relevance
`top_n`	No	Maximum number of top results to return

Implementation Reference

src/tools/jina-tools.ts:829-881 (handler)

Handler function that executes the tool logic by calling Jina's rerank API with the provided query and documents, returning the top relevant results.

async ({ query, documents, top_n }: { query: string; documents: string[]; top_n?: number }) => {
	try {
		const props = getProps();

		const tokenError = checkBearerToken(props.bearerToken);
		if (tokenError) {
			return tokenError;
		}

		if (documents.length === 0) {
			throw new Error("No documents provided for reranking");
		}

		const response = await fetch('https://api.jina.ai/v1/rerank', {
			method: 'POST',
			headers: {
				'Accept': 'application/json',
				'Content-Type': 'application/json',
				'Authorization': `Bearer ${props.bearerToken}`,
			},
			body: JSON.stringify({
				model: 'jina-reranker-v2-base-multilingual',
				query,
				top_n: top_n || documents.length,
				documents
			}),
		});

		if (!response.ok) {
			return handleApiError(response, "Document reranking");
		}

		const data = await response.json() as any;

		// Return each result as individual text items for consistency
		const contentItems: Array<{ type: 'text'; text: string }> = [];

		if (data.results && Array.isArray(data.results)) {
			for (const result of data.results) {
				contentItems.push({
					type: "text" as const,
					text: yamlStringify(result),
				});
			}
		}

		return {
			content: contentItems,
		};
	} catch (error) {
		return createErrorResponse(`Error: ${error instanceof Error ? error.message : String(error)}`);
	}
},

src/tools/jina-tools.ts:824-828 (schema)

Zod schema defining the input parameters for the tool: query (string), documents (array of strings), optional top_n (number).

{
	query: z.string().describe("The query or topic to rank documents against (e.g., 'machine learning algorithms', 'climate change solutions')"),
	documents: z.array(z.string()).describe("Array of document texts to rerank by relevance"),
	top_n: z.number().optional().describe("Maximum number of top results to return")
},

src/tools/jina-tools.ts:820-883 (registration)

Registration of the sort_by_relevance tool on the MCP server, conditional on isToolEnabled, including schema and handler.

if (isToolEnabled("sort_by_relevance")) {
	server.tool(
		"sort_by_relevance",
		"Rerank a list of documents by relevance to a query using Jina Reranker API. Use this when you have multiple documents and want to sort them by how well they match a specific query or topic. Perfect for document retrieval, content filtering, or finding the most relevant information from a collection.",
		{
			query: z.string().describe("The query or topic to rank documents against (e.g., 'machine learning algorithms', 'climate change solutions')"),
			documents: z.array(z.string()).describe("Array of document texts to rerank by relevance"),
			top_n: z.number().optional().describe("Maximum number of top results to return")
		},
		async ({ query, documents, top_n }: { query: string; documents: string[]; top_n?: number }) => {
			try {
				const props = getProps();

				const tokenError = checkBearerToken(props.bearerToken);
				if (tokenError) {
					return tokenError;
				}

				if (documents.length === 0) {
					throw new Error("No documents provided for reranking");
				}

				const response = await fetch('https://api.jina.ai/v1/rerank', {
					method: 'POST',
					headers: {
						'Accept': 'application/json',
						'Content-Type': 'application/json',
						'Authorization': `Bearer ${props.bearerToken}`,
					},
					body: JSON.stringify({
						model: 'jina-reranker-v2-base-multilingual',
						query,
						top_n: top_n || documents.length,
						documents
					}),
				});

				if (!response.ok) {
					return handleApiError(response, "Document reranking");
				}

				const data = await response.json() as any;

				// Return each result as individual text items for consistency
				const contentItems: Array<{ type: 'text'; text: string }> = [];

				if (data.results && Array.isArray(data.results)) {
					for (const result of data.results) {
						contentItems.push({
							type: "text" as const,
							text: yamlStringify(result),
						});
					}
				}

				return {
					content: contentItems,
				};
			} catch (error) {
				return createErrorResponse(`Error: ${error instanceof Error ? error.message : String(error)}`);
			}
		},
	);
}

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