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yantrix-ai

@praveen030686/data-apis-mcp

Extract Contacts from URL

web_extract_contacts
Read-onlyIdempotent

Extract emails, phone numbers, and social media links from web pages to collect contact information from any URL.

Instructions

Extract emails, phone numbers, and social media links from any web page. Costs $0.03 USDC per request via x402 on Base.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL to extract contacts from

Implementation Reference

  • The async handler function that calls the web_extract_contacts API.
    async ({ url }) => {
      const data = await apiPost(`${WEB_EXTRACT_API}/api/v1/extract/contacts`, { url });
      return { content: [{ type: "text", text: JSON.stringify(data, null, 2) }] };
    }
  • src/index.ts:302-317 (registration)
    Tool registration for web_extract_contacts including title, description, and input schema.
    server.registerTool(
      "web_extract_contacts",
      {
        title: "Extract Contacts from URL",
        description: `Extract emails, phone numbers, and social media links from any web page.
    Costs $0.03 USDC per request via x402 on Base.`,
        inputSchema: {
          url: z.string().url().describe("URL to extract contacts from"),
        },
        annotations: { readOnlyHint: true, destructiveHint: false, idempotentHint: true, openWorldHint: true },
      },
      async ({ url }) => {
        const data = await apiPost(`${WEB_EXTRACT_API}/api/v1/extract/contacts`, { url });
        return { content: [{ type: "text", text: JSON.stringify(data, null, 2) }] };
      }
    );
Behavior4/5

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

Annotations already provide safety information (readOnlyHint, non-destructive), but the description adds valuable behavioral context not covered by annotations: the monetary cost per request ($0.03 USDC via x402 on Base). This is critical operational information that helps the agent understand the tool's usage implications.

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 extremely concise with just two sentences that each serve distinct purposes: the first explains what the tool does, the second explains the cost. There's zero wasted language, and the most important information (the extraction capability) is front-loaded.

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?

For a single-parameter tool with comprehensive annotations and clear purpose, the description provides adequate context. The cost disclosure is particularly valuable. The main gap is the lack of output format information (no output schema exists), but given the tool's relative simplicity and good annotations, this is a minor limitation.

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?

The input schema has 100% description coverage with a clear parameter description for 'url'. The description doesn't add any additional parameter semantics beyond what's already in the schema, but with complete schema coverage, a baseline score of 3 is appropriate.

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 specific action ('extract') and resources ('emails, phone numbers, and social media links') from a specific source ('any web page'). It distinguishes itself from sibling tools like web_extract_text or web_extract_metadata by focusing specifically on contact information extraction.

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

Usage Guidelines3/5

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

The description implies usage context (extracting contact data from web pages) but doesn't explicitly state when to use this tool versus alternatives like web_extract_structured or web_extract_batch. No guidance is provided on prerequisites, limitations, or exclusions beyond the cost mention.

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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