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wlmwwx

Jina AI Remote MCP Server

by wlmwwx

search_web

Search the web for current information, news, articles, and websites to answer questions about recent events, research topics, or find specific resources.

Instructions

Search the entire web for current information, news, articles, and websites. Use this when you need up-to-date information, want to find specific websites, research topics, or get the latest news. Ideal for answering questions about recent events, finding resources, or discovering relevant content.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch terms or keywords to find relevant web content (e.g., 'climate change news 2024', 'best pizza recipe'). Can be a single query string or an array of queries for parallel search.
numNoMaximum number of search results to return, between 1-100
tbsNoTime-based search parameter, e.g., 'qdr:h' for past hour, can be qdr:h, qdr:d, qdr:w, qdr:m, qdr:y
locationNoLocation for search results, e.g., 'London', 'New York', 'Tokyo'
glNoCountry code, e.g., 'dz' for Algeria
hlNoLanguage code, e.g., 'zh-cn' for Simplified Chinese

Implementation Reference

  • Registers the 'search_web' MCP tool, providing name, description, Zod input schema, and inline handler function.
    server.tool(
    	"search_web",
    	"Search the entire web for current information, news, articles, and websites. Use this when you need up-to-date information, want to find specific websites, research topics, or get the latest news. Ideal for answering questions about recent events, finding resources, or discovering relevant content. 💡 Tip: Use `parallel_search_web` if you need to run multiple searches simultaneously.",
    	{
    		query: z.string().describe("Search terms or keywords to find relevant web content (e.g., 'climate change news 2024', 'best pizza recipe')"),
    		num: z.number().default(30).describe("Maximum number of search results to return, between 1-100"),
    		tbs: z.string().optional().describe("Time-based search parameter, e.g., 'qdr:h' for past hour, can be qdr:h, qdr:d, qdr:w, qdr:m, qdr:y"),
    		location: z.string().optional().describe("Location for search results, e.g., 'London', 'New York', 'Tokyo'"),
    		gl: z.string().optional().describe("Country code, e.g., 'dz' for Algeria"),
    		hl: z.string().optional().describe("Language code, e.g., 'zh-cn' for Simplified Chinese")
    	},
    	async ({ query, num, tbs, location, gl, hl }: SearchWebArgs) => {
    		try {
    			const props = getProps();
    
    			const tokenError = checkBearerToken(props.bearerToken);
    			if (tokenError) {
    				return tokenError;
    			}
    
    			const searchResult = await executeWebSearch({ query, num, tbs, location, gl, hl }, props.bearerToken);
    
    			return {
    				content: formatSingleSearchResultToContentItems(searchResult),
    			};
    		} catch (error) {
    			return createErrorResponse(`Error: ${error instanceof Error ? error.message : String(error)}`);
    		}
    	},
    );
  • MCP tool handler for 'search_web': validates bearer token, calls executeWebSearch utility, formats result with formatSingleSearchResultToContentItems, handles errors.
    async ({ query, num, tbs, location, gl, hl }: SearchWebArgs) => {
    	try {
    		const props = getProps();
    
    		const tokenError = checkBearerToken(props.bearerToken);
    		if (tokenError) {
    			return tokenError;
    		}
    
    		const searchResult = await executeWebSearch({ query, num, tbs, location, gl, hl }, props.bearerToken);
    
    		return {
    			content: formatSingleSearchResultToContentItems(searchResult),
    		};
    	} catch (error) {
    		return createErrorResponse(`Error: ${error instanceof Error ? error.message : String(error)}`);
    	}
    },
  • Zod schema defining input parameters for the search_web tool.
    {
    	query: z.string().describe("Search terms or keywords to find relevant web content (e.g., 'climate change news 2024', 'best pizza recipe')"),
    	num: z.number().default(30).describe("Maximum number of search results to return, between 1-100"),
    	tbs: z.string().optional().describe("Time-based search parameter, e.g., 'qdr:h' for past hour, can be qdr:h, qdr:d, qdr:w, qdr:m, qdr:y"),
    	location: z.string().optional().describe("Location for search results, e.g., 'London', 'New York', 'Tokyo'"),
    	gl: z.string().optional().describe("Country code, e.g., 'dz' for Algeria"),
    	hl: z.string().optional().describe("Language code, e.g., 'zh-cn' for Simplified Chinese")
    },
  • Core helper function implementing the web search logic: sends POST request to Jina's search API (https://svip.jina.ai/) with query parameters and bearer token.
    export async function executeWebSearch(
        searchArgs: SearchWebArgs,
        bearerToken: string
    ): Promise<SearchResultOrError> {
        try {
            const response = await fetch('https://svip.jina.ai/', {
                method: 'POST',
                headers: {
                    'Accept': 'application/json',
                    'Content-Type': 'application/json',
                    'Authorization': `Bearer ${bearerToken}`,
                },
                body: JSON.stringify({
                    q: searchArgs.query,
                    num: searchArgs.num || 30,
                    ...(searchArgs.tbs && { tbs: searchArgs.tbs }),
                    ...(searchArgs.location && { location: searchArgs.location }),
                    ...(searchArgs.gl && { gl: searchArgs.gl }),
                    ...(searchArgs.hl && { hl: searchArgs.hl })
                }),
            });
    
            if (!response.ok) {
                return { error: `Search failed for query "${searchArgs.query}": ${response.statusText}` };
            }
    
            const data = await response.json() as any;
            return { query: searchArgs.query, results: data.results || [] };
        } catch (error) {
            return { error: `Search failed for query "${searchArgs.query}": ${error instanceof Error ? error.message : String(error)}` };
        }
    }
  • TypeScript interface SearchWebArgs defining the structure of input arguments for web search, imported and used for typing the handler.
    export interface SearchWebArgs {
        query: string;
        num?: number;
        tbs?: string;
        location?: string;
        gl?: string;
        hl?: string;
    }
  • Helper function to format a single search result (or error) into MCP-standard content items (YAML text blocks). Called by the tool handler.
    export function formatSingleSearchResultToContentItems(searchResult: SearchResultOrError): Array<{ type: 'text'; text: string }> {
        if ('error' in searchResult) {
            return [{
                type: "text" as const,
                text: `Error: ${searchResult.error}`,
            }];
        }
    
        return formatSearchResultsToContentItems(searchResult.results);
    }
Behavior3/5

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 mentions the tool searches for 'current information' and is 'ideal for answering questions about recent events,' which implies up-to-date results, but lacks details on rate limits, authentication needs, result format, or pagination. The description adds some behavioral context but doesn't fully compensate for the absence of annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, starting with the core purpose. It uses two sentences efficiently, with the second sentence providing usage guidelines without redundancy. Every sentence adds value, though it could be slightly more structured for clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (6 parameters, no annotations, no output schema), the description is moderately complete. It covers purpose and usage well but lacks details on behavioral traits like result format, error handling, or limitations. Without annotations or output schema, more context on what to expect from results would improve completeness.

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 6 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, such as examples or usage tips. With high schema coverage, the baseline is 3, as the description doesn't enhance parameter understanding.

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 with specific verbs ('search the entire web') and resources ('current information, news, articles, websites'). It distinguishes from siblings by specifying web search versus academic (arxiv/ssrn), image search, or URL operations, making the scope explicit.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool ('when you need up-to-date information, want to find specific websites, research topics, or get the latest news') and includes ideal use cases ('answering questions about recent events, finding resources, or discovering relevant content'). It implicitly distinguishes from siblings by focusing on general web content versus specialized sources.

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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