What configuration is required to use the server?
You must provide a Loxo API key (`LOXO_API_KEY`) and your agency slug (`LOXO_AGENCY_SLUG`). The `LOXO_DOMAIN` is optional and defaults to `app.loxo.co`.
Loxo MCP Server
@tbensonwest
Basic information
About Loxo MCP Server
No overview available yet
Loxo MCP Server config
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
RepositoryLoxo MCP Server tools
Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is Loxo MCP Server?
The Loxo MCP Server is a Model Context Protocol (MCP) server that provides tools for interacting with the Loxo recruitment platform API. It enables AI assistants to perform recruitment tasks such as managing candidates, jobs, activities, and call queues.
How to use Loxo MCP Server?
Install by cloning the repository, running npm install and npm run build. Configure the .env file with your Loxo API key, agency slug, and optionally the domain (defaults to app.loxo.co). Start the server with npm start or use npm run dev for watch mode.
Key features of Loxo MCP Server
- Schedule and log activities for candidates or jobs
- Search and retrieve candidate and job details
- Add notes to candidates and jobs
- Manage the call queue (view and add entries)
- Retrieve activity types and today’s tasks
- Uses Zod for runtime type validation
Use cases of Loxo MCP Server
- Search for candidates in the Loxo database
- Get detailed information about a specific job
- Log an activity for a candidate or job
- View and manage the current call queue
- List all tasks and scheduled activities for today
Frequently asked questions
What runtime type validation does the server use?
The server uses Zod to validate environment variables, tool input parameters, and API responses.
How does the server communicate with AI assistants?
It communicates over stdio using the Model Context Protocol SDK for seamless integration with AI assistants.
What error handling is included?
The server handles environment validation errors, API request failures, invalid tool parameters, and unknown tool requests.
What categories of tools are available?
Tools are grouped into activity management, call queue management, candidate management, and job management.
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