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Reach MCP — LinkedIn for AI agents

scrape_search

Read-onlyIdempotent

Run one page of a LinkedIn, Sales Navigator, or Recruiter search and return normalized profile rows. Pass the full search URL. Use start+count to paginate (count ignored for standard LinkedIn, fixed ~10/page).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFull LinkedIn / SalesNav / Recruiter search URL.
countNoPage size (max 25). Ignored for standard LinkedIn.
startNoPagination offset.
account_idYesReach id of the LinkedIn account to act on, from list_accounts.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoRequested page size.
itemsNo
startNoOffset used for this request.
totalNoTotal results reported by LinkedIn.
next_startNoPass as ``start`` for the next page when present.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context: it runs exactly one page, returns normalized rows, and has platform-specific pagination behavior (count ignored for standard LinkedIn, fixed ~10/page). This goes beyond the annotations without contradicting them.

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?

Three sentences with zero waste. The core action and input are front-loaded, and the pagination caveat is stated compactly. Every sentence earns its place.

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?

The description is complete for a read-only, idempotent pagination tool. It explains the input, the pagination behavior, and the output shape. The only minor gap is that it doesn't describe the exact structure of the normalized profile rows, but an output schema exists, so that burden is already carried by structured data.

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 adds the pagination semantics (start+count, count ignored for standard LinkedIn) and clarifies that account_id comes from list_accounts, but the schema already covers the basics. Baseline 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 states a specific verb ('Run'), a specific resource ('one page of a LinkedIn, Sales Navigator, or Recruiter search'), and the output ('normalized profile rows'). It also names the input ('full search URL'), which distinguishes it from sibling tools like salesnav_build_search_url (which builds URLs) and scrape_profile (which scrapes a single profile).

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 explicitly says to pass the full search URL and explains pagination with start+count, including the caveat that count is ignored for standard LinkedIn. This gives clear when-to-use guidance and distinguishes it from URL-building and profile-scraping siblings.

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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