arifur9993/attendance-engine-mcp
by Various
MCP server giving AI agents tools for workforce attendance, overtime, overnight shifts & California wage-and-hour compliance.
MCP
arifur9993/attendance-engine-mcp
Added 1 June 2026
Overview
An MCP server that exposes tools for AI agents to handle workforce attendance, overtime, overnight shifts, and California wage-and-hour compliance. Built in TypeScript, it provides a structured interface for agents to query and manage attendance data.
Best for
Best for
Developers building AI agents for HR compliance and attendance management in California
Use cases
- Integrate AI agents with HR systems to automate attendance tracking
- Enforce California overtime and meal-break rules via agent workflows
- Build compliance checks for overnight shift scheduling
Notes
An MCP server that exposes tools for AI agents to handle workforce attendance, overtime, overnight shifts, and California wage-and-hour compliance. Built in TypeScript, it provides a structured interface for agents to query and manage attendance data.
0 stars on GitHub. Last updated 2026-05-30. Licensed MIT.
Use cases
- Integrate AI agents with HR systems to automate attendance tracking
- Enforce California overtime and meal-break rules via agent workflows
- Build compliance checks for overnight shift scheduling
Pros
- Specialized for California wage-and-hour law, reducing compliance risk
- Leverages MCP protocol for easy integration with AI agent frameworks
- TypeScript codebase offers type safety and broad ecosystem support
Cons
- No stars or community adoption yet, indicating early-stage or untested
- Limited to California regulations, not applicable to other jurisdictions
- Requires an MCP-compatible agent runtime to be useful
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Specialized for California wage-and-hour law, reducing compliance risk
- Leverages MCP protocol for easy integration with AI agent frameworks
- TypeScript codebase offers type safety and broad ecosystem support
Cons
- No stars or community adoption yet, indicating early-stage or untested
- Limited to California regulations, not applicable to other jurisdictions
- Requires an MCP-compatible agent runtime to be useful
Pairs with
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