Payroll MCP Server

Payroll MCP Server – Overview

The Payroll MCP Server is a TypeScript‑based implementation of the Model Context Protocol (MCP) designed to bridge AI assistants with payroll and employee data systems. By exposing a set of well‑defined resources, tools, prompts, and an SSE endpoint, the server allows large language models to query and manipulate payroll information in a secure, standardized manner. This solves the common problem of integrating legacy HR or accounting APIs into conversational AI workflows without requiring custom adapters for each model.

At its core, the server provides a RESTful API backed by Express that implements the MCP contract. Clients can connect via Server‑Sent Events () for real‑time, bidirectional communication or post messages to to trigger tool execution. The server authenticates requests using either API keys (/) or partner credentials (/), giving organizations flexibility to enforce access controls that match their existing security posture. Once authenticated, an LLM can invoke tools such as , , or to retrieve employee records, compute gross and net pay, or fetch basic profile data—all within a single conversational turn.

Key capabilities include:

• Dynamic resources () that return up‑to‑date employee data.
• Static resources () for quick onboarding messages.
• A set of tool endpoints that encapsulate common payroll operations, each with clear input schemas and authentication requirements.
• Prompt templates () that help the model formulate queries against the underlying data sources.
• Real‑time SSE support for streaming responses, enabling smooth conversational experiences.

Typical use cases span a range of industries: an HR chatbot that can answer employee queries about salary, tax deductions, or leave balances; a finance assistant that auto‑generates payroll reports for auditors; or an internal tool where developers can prototype new payroll features by simply invoking MCP tools from their preferred LLM. Because the server follows the MCP specification, any model that understands MCP—Claude, GPT‑4o, or others—can be wired up with minimal configuration, eliminating the need for bespoke integrations.

In summary, the Payroll MCP Server turns complex payroll APIs into consumable AI actions. It delivers a secure, type‑safe interface for developers, while giving conversational agents the ability to perform real business logic on behalf of users. This combination accelerates development, reduces maintenance overhead, and ensures that sensitive payroll data remains protected behind robust authentication mechanisms.