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LinkMCP: hosted LinkedIn MCP server

Bulk Get Profiles

linkedin_bulk_get_profiles
Read-onlyIdempotent

Fetch LinkedIn profiles in bulk (up to 10). detail: "slim" (default) returns name, headline, location, current position and counts. detail: "full" returns the same full profile as linkedin_get_profile (about, all positions with descriptions, all education, industry, followers and connections). Both cost the same per profile as linkedin_get_profile: one profile lookup each. Company details are not included; use linkedin_get_company. Returns per-item results and never stops on the first error.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
detailNo"slim" (default): name, headline, location, current position and counts. "full": the same full profile as linkedin_get_profile, at the same cost per profile.slim
identifiersYesArray of LinkedIn profile identifiers (URLs, public IDs / slugs, or URNs). 1–10 items.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, openWorld, non-destructive), so the description's added value is the cost model ('one profile lookup each'), the detail-level output tradeoff, and the critical error-handling contract ('Returns per-item results and never stops on the first error'). That failure-mode disclosure is exactly the kind of trait an agent needs and the annotations cannot express.

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?

Front-loaded with purpose and limit, then detail modes, then cost, then exclusions, then error behavior - a logical ordering. It is denser than strictly necessary (the detail definition is repeated in the schema), but each sentence carries distinct information.

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?

With no output schema, the description compensates by enumerating what each detail mode returns and by specifying the partial-success error semantics. Nothing an agent needs to call it correctly is missing, though response shape for per-item errors (error object fields) remains unspecified.

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%, and the enum for 'detail' is documented in both the schema and the description with essentially the same content. The description adds cost equivalency and a pointer to linkedin_get_profile for the 'full' shape, but no new syntax or identifier-format detail beyond the schema, so the baseline 3 applies.

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?

States a specific verb and resource ('Fetch LinkedIn profiles in bulk (up to 10)') and immediately distinguishes itself from the single-profile sibling by defining both detail modes. The scope (bulk, max 10, cost per profile) is unambiguous and an agent can pick it apart from linkedin_get_profile without opening either schema.

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

Usage Guidelines4/5

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

Gives clear routing conditions: use this for 1-10 profile lookups at the same cost as linkedin_get_profile, and use linkedin_get_company when company details are needed. It stops short of saying when a single call is preferable to bulk (e.g. for one identifier), so it is clear context rather than full when/when-not guidance.

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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