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linkfetch-mcp

by ffucucuoglu

linkfetch_get_profile

Fetch a full LinkedIn profile by URL or public identifier slug, returning work history, education, and skills. On a cache miss, it asks users to capture the profile with LinkFetch Chrome extension.

Instructions

Fetch a full LinkedIn profile (name, headline, about, work history, education, skills, certifications) by LinkedIn URL or public identifier slug. Provide exactly one of url or slug. Cache-first: on miss, returns an extension_required error instructing the user to capture via the LinkFetch Chrome extension.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoA linkedin.com/in/<slug> profile URL, e.g. https://www.linkedin.com/in/reidhoffman/
slugNoBare public identifier (the tail of /in/<slug>), e.g. 'reidhoffman'. Use instead of `url`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description must carry the behavioral burden, and it discloses a genuinely important failure mode: cache-first with an `extension_required` error on miss instructing use of the Chrome extension. It omits auth prerequisites and any rate-limit behavior, which is notable given sibling safety tools exist.

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?

Two sentences, zero filler. The capability and input contract come first, the cache/error caveat second — correctly 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?

Enumerates the return payload in lieu of an output schema and covers the error path, so an agent can act correctly. Missing only prerequisite/permission context and rate-limit awareness, which matter for a scraper-style tool in this toolset.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so 3 is the baseline, but the description adds real value the schema cannot express: the mutual-exclusivity constraint 'exactly one of url or slug', which is not encoded as a oneOf in the schema.

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?

Specific verb+resource ('Fetch a full LinkedIn profile') with an explicit enumeration of the returned fields and the two accepted identifiers. It is trivially distinguishable from siblings like linkfetch_search_people or linkfetch_get_company.

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 invocation context ('Provide exactly one of `url` or `slug`') and states the cache-first path. It does not, however, tell the agent when to prefer this over linkfetch_search_people (search vs. direct fetch) or what happens on a cache hit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.