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Workable Launches MCP Server for AI-Powered Recruiting and HR Workflows

By: Workable via GlobeNewswire
May 13, 2026 at 07:21 AM EDT
ⓘ This article is third-party content and does not represent the views of this site. We make no guarantees regarding its accuracy or completeness.

BOSTON, May 13, 2026 (GLOBE NEWSWIRE) -- Workable, a leading essential HR software and talent acquisition software platform serving more than 6,200 companies across 100+ countries, announced the general availability of the Workable MCP Server. Built on the Model Context Protocol, an open standard that connects AI assistants to external data sources, the integration gives any compatible AI assistant direct read and write access to a company's live Workable data: jobs, candidates, pipeline stages, offers, requisitions, employees, time tracking and time-off records, and calendar events.

The Workable MCP Server ships with 38 MCP tools spanning the full scope of recruiting and HR workflows. Workable is among the first top recruiting platforms to offer a native MCP integration of this breadth, and to include it at no additional cost across all subscription plans.

What the Workable MCP Server Does

The Model Context Protocol is an open standard, originally developed by Anthropic, that enables conversational AI assistants to connect to external tools and live data through a standardized interface. The Workable MCP Server implements this standard, enabling AI assistants including Claude (Anthropic) and ChatGPT (OpenAI) to query and act on Workable data directly through natural language processing — with no exports, no spreadsheets, and no tab-switching required.

A recruiter managing multiple open roles could ask: "Which engineering candidates have been in the phone screen stage for more than a week?" The AI queries Workable’s live HR analytics and returns an answer immediately. The same conversational AI interface can be used to review requisition approvals, check pending time-off requests, or surface candidates by pipeline stage across any number of active roles — turning routine task automation into a natural conversation.

Setup takes minutes. Users add a custom connector in their AI tool of choice and authenticate via OAuth2. No developer involvement is required, and no API keys need to be managed.

Security and Permission Scoping

The Workable MCP Server respects each user's existing access permissions. Every AI session is scoped to the authenticated user's role and job assignments within Workable. The AI can only read and act on data the user is already authorized to see. No data is shared beyond what the individual user's permissions allow.

Availability

The Workable MCP Server is available now for all customers on all Workable plans. Setup documentation and a step-by-step walkthrough are available at workable.com. Existing customers with questions should contact their account manager.

About Workable

Workable is a leading recruiting, HR, and talent management platform that supports the entire hiring-to-employment lifecycle. Recognized by Forbes Advisor as a top-rated AI-driven applicant tracking system and talent acquisition software solution, Workable helps more than 6,200 companies across 100+ countries streamline hiring and employee management.

With Workable, teams can post jobs across 200+ job posting platforms, source from 400+ million candidate profiles, screen and interview applicants, manage employee referral programs, extend offers, onboard new hires, and manage employees — including employee evaluation and performance reviews — all from a single platform. The platform includes a powerful ATS, an HRIS with time tracking, time-off management, and HR analytics capabilities, and an autonomous AI Recruiting Agent launched earlier this year.

Founded in Athens in 2012, Workable has supported more than 2.1 million hires and processed over 930 billion AI tokens.

Media Contact:

Brendan Jeannetti
Brendan.Jeannetti@workable.com

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/514c6a69-6edc-4085-9b6e-3fae732d70ba


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