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automcp-app

Linkd MCP Server

by automcp-app

enrich_linkedin

Retrieve detailed profile information from LinkedIn URLs to enrich contact data and support business intelligence workflows.

Instructions

Retrieves detailed profile information for a specific LinkedIn URL. Each successful lookup costs 1 credit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe LinkedIn profile URL to look up.

Implementation Reference

  • The async handler function executing the core logic of the 'enrich_linkedin' tool: constructs API URL, calls makeLinkdRequest, processes response, and returns formatted content.
    export const enrichLinkedinTool = async ({
      url,
    }: EnrichLinkedinParams) => {
      const apiUrl = new URL("https://search.linkd.inc/api/enrich/linkedin");
      apiUrl.searchParams.append("url", url);
    
      const response = await makeLinkdRequest(apiUrl.toString(), {});
      const responseData = await response.json();
    
      if (responseData.error) {
        throw new Error(
          `Failed to enrich LinkedIn profile: ${JSON.stringify(responseData.error)}`
        );
      }
    
      return {
        content: [
          {
            type: "text" as const,
            text: `enrichment completed successfully: ${JSON.stringify(responseData, null, 2)}`
          }
        ]
      };
    };
  • Zod input schema and TypeScript type definition for the tool's parameters (LinkedIn URL). Includes name and description exports nearby.
    export const enrichLinkedinSchema = {
      url: z.string().describe("The LinkedIn profile URL to look up."),
    };
    
    type EnrichLinkedinParams = {
      url: string;
    };
  • Registration of the 'enrich_linkedin' tool on the MCP server using the imported name, description, schema, and handler.
      enrichLinkedinName,
      enrichLinkedinDescription,
      enrichLinkedinSchema,
      enrichLinkedinTool
    );
  • Tool name and description constants used for registration and documentation.
    export const enrichLinkedinName = "enrich_linkedin";
    
    export const enrichLinkedinDescription = "Retrieves detailed profile information for a specific LinkedIn URL. Each successful lookup costs 1 credit.";
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: the operation is a retrieval (not creation or update), it involves a cost ('1 credit per successful lookup'), and it requires a specific URL. However, it lacks details on error handling, rate limits, or authentication needs.

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 front-loaded with the core purpose in the first sentence and adds critical cost information in the second, with no wasted words. Every sentence earns its place by providing essential information efficiently.

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 no annotations, no output schema, and a simple input schema, the description is adequate but has gaps. It covers purpose and cost but lacks details on return values, error cases, or performance characteristics, which would help an agent use it more effectively.

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 the 'url' parameter fully. The description adds no additional meaning or context beyond what the schema provides, such as URL format examples or validation rules, meeting the baseline for high coverage.

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 ('Retrieves detailed profile information') and target resource ('for a specific LinkedIn URL'), distinguishing it from sibling tools like 'scrape_linkedin' or 'search_for_users' which imply different operations or scopes.

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 when detailed LinkedIn profile data is needed from a specific URL, but it does not explicitly state when to use this tool versus alternatives like 'scrape_linkedin' or 'search_for_users', nor does it mention prerequisites or exclusions.

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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