Open-source MCP server for PrismHR. PEO workflow tools + Microsoft 365 connectors.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"prismhr-mcp": {
"env": {
"PRISMHR_MCP_PEO_ID": "<your-peo-id>",
"PRISMHR_MCP_PASSWORD": "<paste or reference>",
"PRISMHR_MCP_USERNAME": "<your-api-username>",
"PRISMHR_MCP_ENVIRONMENT": "uat"
},
"args": [
"run",
"--directory",
"C:\\path\\to\\prismhr-mcp",
"prismhr-mcp"
],
"command": "uv"
}
}
}Are you the author?
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The open-source Model Context Protocol (MCP) server for PrismHR. Connect Claude, Cursor, or any MCP-compatible AI agent directly to your PrismHR PEO platform. Automate payroll, benefits enrollment, compliance reporting, AR/billing, carrier EDI files, and Microsoft 365 actions — with verified-schema tools, scope-gated consent, and zero custom integration code.
No automated test available for this server. Check the GitHub README for setup instructions.
Five weighted categories — click any category to see the underlying evidence.
No known CVEs.
No package registry to scan.
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The open-source Model Context Protocol (MCP) server for PrismHR. Connect Claude, Cursor, or any MCP-compatible AI agent directly to your PrismHR PEO platform. Automate payroll, benefits enrollment, compliance reporting, AR/billing, carrier EDI files, and Microsoft 365 actions — with verified-schema tools, scope-gated consent, and zero custom integration code.
Built for PEOs, brokers, and payroll operators who want AI agents that actually work against PrismHR — not another brittle script farm.
Maintained by Simploy. MIT-licensed, PyPI-distributed, plugin-friendly. The fundamental layer for PrismHR × agentic AI.
mcp-name: io.github.nikulk2992-jpg/prismhr-mcp
Keywords: PrismHR API, PrismHR integration, MCP server, Model Context Protocol, PEO automation, payroll automation, AI for HR, Claude for PrismHR, agentic AI, benefits enrollment automation, 834 EDI, 401(k) file automation, HRIS AI agent, PEO software integration.
Every PEO running PrismHR ends up with the same Frankenstein stack: Python
scripts, Postman collections, Playwright automations, one-off Node apps.
Each one re-implements login, session keepalive, retry logic, pagination,
and PrismHR's quirks (camelCase schemas, 500 "No data found" gotchas,
batch-of-20 caps, silent 401s).
prismhr-mcp centralizes all of that once, as a production-grade MCP server.
The AI agent orchestrates; the server owns auth, caching, retries,
normalization, and PEO domain logic. Any PEO drops it in and gets a
productive AI experience against their own PrismHR tenant — no glue code,
no guesswork, no hallucinated endpoints.
Who this is for:
Production-ready core. Live on PyPI and the MCP Registry.
meta_call lets the agent invoke any verified method safely.PRISMHR_MCP_ALLOW_PROD=true required to
point at prod PrismHR. Prevents accidental first-run blast radius.See .planning/architecture.md for the full roadmap and
.planning/assistants-roadmap.md for the paid tier details.
Once wired into your PrismHR tenant, an AI agent (Claude, ChatGPT, Cursor) can run any of these workflows against live data — read-only by default, write actions opt-in and scoped.