Skip to main content
Glama
HRIS MCP Connector

HRIS MCP Connector

HRIS MCP Connector

A Model Context Protocol (MCP) server that gives an AI client like Claude Desktop read-only access to HR information system data through a typed tool layer. Built with the official Python MCP SDK.

This public repository is a reference implementation backed by a synthetic mock data layer. The production version swaps that layer for authenticated calls to a real HRIS such as Rippling, leaving the tool surface identical. No real employee data, no credentials, and no vendor-specific configuration are included here.

What It Does

It exposes four read-only tools to an MCP client:

Tool

What it returns

list_recent_hires

Employees who started within the last N days, newest first

get_employee

A single employee record by ID

list_departments

Each department with its current headcount

get_pto_balance

Remaining paid-time-off hours for one employee

Ask Claude something like "who joined in the last two weeks?" and it calls list_recent_hires and answers from the result.

Related MCP server: OCP AI Custom HR MCP Server

Why It's Built This Way

Read-only by design. Every tool retrieves information; none changes HR data. Write actions belong behind authentication, authorization, audit logging, and human approval, which are deliberately out of scope for a public reference server.

A clean tool surface over a swappable data layer. The MCP tools call plain functions in mock_data.py. In production, that one module is replaced with real HRIS API calls and nothing else changes. That separation is the whole point: the AI client sees a stable contract regardless of what's behind it.

Testable without a server. Because the query logic lives in plain functions, the test suite checks it directly with a fixed reference date. No process, no network, no flakiness. See tests/.

Protocol-safe logging. This is a stdio server, so stdout carries the protocol. All diagnostics go to stderr, which keeps the message stream clean.

Architecture

flowchart LR
    C[Claude / MCP Client] --> S[MCP Server: tools]
    S --> D[Data Layer]
    D --> M[Mock Data]
    D -. production .-> API[Real HRIS API]

Setup

  1. pip install -r requirements.txt

  2. Run the server: python src/server.py

Connect it to Claude Desktop

Add this to your Claude Desktop config file, using the absolute path to this repo:

{
  "mcpServers": {
    "hris-connector": {
      "command": "python",
      "args": ["/absolute/path/to/hris-mcp-connector/src/server.py"]
    }
  }
}

Restart Claude Desktop fully (quit, don't just close the window). The four tools then appear in the client.

Going to Production

To connect a real HRIS, replace the functions in src/mock_data.py with authenticated API calls. The API token goes in a .env file (see .env.example), which is gitignored and never committed. The tool definitions in src/server.py stay exactly as they are.

Status

Reference implementation with a mock data layer. A production version of this connector runs against a live HRIS in a real HR environment; this public repository contains the pattern and the mock layer only.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    Related MCP Connectors

    Related MCP Servers

    • F
      license
      Not graded
      quality
      D
      maintenance
      An MCP server for interacting with an HR database, enabling querying employee data and HR operations via natural language.
      -
    • F
      license
      Not graded
      quality
      C
      maintenance
      Exposes SAP SuccessFactors HR data as MCP tools for AI agents, enabling natural language queries about employees, jobs, performance, and organizational structure.
      -
    • F
      license
      Not graded
      quality
      D
      maintenance
      Enables natural-language-based employee leave management including leave balance checks, leave applications, approvals, and history retrieval through an MCP-compatible client.
      -