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Multi-ATS Jobs MCP Server

search_jobs

Fetch live, normalized open job postings for one or more companies across 7 keyless ATS platforms (Greenhouse, Lever, Ashby, SmartRecruiters, Workday, Recruitee, Workable). Platform and board token are auto-detected from a bare slug or domain. Returns a unified schema: title, company, location, remote, url, source_platform, posted_at. Free. Derived layers (normalized comp, hiring-intent) and a hosted 10-ATS feed are metered — call get_premium_access.

Input Schema

NameRequiredDescriptionDefault
companiesYesCompany slugs ("stripe"), domains ("stripe.com"), or explicit "platform:token" (e.g. "ashby:openai"). 1-25 entries.
maxPerCompanyNoCap postings returned per company (default 25, max 200).
includeDescriptionNoInclude full job description text when true (default false).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the keyless/no-auth model, that this is free while derived layers are metered, and that platform/board token are auto-detected, so the agent knows a bare slug is acceptable. It omits rate limits, pagination behavior beyond the per-company cap, and error/failure modes, which keeps it short of a 5.

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 the core action, then platform coverage, return shape, and pricing in a logical order. Dense but nearly every sentence carries information; the platform enumeration and return-field list are long but justified by what they disambiguate.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, and the description enumerates the unified return fields (title, company, location, remote, url, source_platform, posted_at), so an agent knows exactly what comes back. With three well-documented parameters and a stated free/metered boundary, nothing material is missing.

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 coverage is 100%, so baseline 3 applies. The description reinforces the auto-detection semantics for the companies parameter (bare slug or domain), but adds no format or constraint detail beyond what the schema already documents for maxPerCompany and includeDescription.

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 live, normalized open job postings') and bounds scope precisely (one or more companies, 7 named ATS platforms). An agent can distinguish it from siblings like resolve_company or list_platforms 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?

Clear context: use this to get actual postings, and it explicitly routes the agent to get_premium_access for derived layers and the 10-ATS hosted feed. It does not explicitly state when to use resolve_company or list_platforms first, so the alternative-selection guidance is incomplete rather than absent.

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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