I build an AI agent using StackOne MCP

prathyusha k — Tue, 05 May 2026 21:18:19 +0000

Hello myself Prathyusha. When I decided to apply to StackOne, I did not send
a resume first. I built something with their platform first.

This is the story of building an AI agent using StackOne MCP.

What I Built

An AI agent that onboards a new employee across
4 enterprise platforms automatically — using
StackOne MCP as the single integration gateway.

One command does everything:

npm run onboard --
example employee name: Priya Sharma

Output:

Step 1: Fetching candidate... ✓ Priya Sharma
Step 2: Creating BambooHR record... ✓ Employee #115
Step 3: Creating Notion page... ✓ Checklist created
Step 4: Sending Slack message... ✓ Team notified

Onboarding complete in seconds.
Audit trail written to audit-log.json.

The Problem It Solves

Most companies onboard employees manually:

HR types data into BambooHR by hand.
Someone creates a Notion doc from scratch.
Manager writes a Slack welcome manually.
IT gets notified separately.

That is 2 to 4 hours of manual work per new hire.
This agent does all of it in seconds.

What is StackOne MCP?

MCP stands for Model Context Protocol.
It is an open standard that lets AI agents
connect to external tools in a structured way.

Without StackOne:
Agent → custom code → BambooHR
Agent → different code → Notion
Agent → another code → Slack

With StackOne MCP:
Agent → ONE endpoint → BambooHR
→ Notion
→ Slack

One API key. One endpoint. 260+ integrations.
Auth, retries, and audit logging handled
automatically by StackOne's Falcon engine.

The Architecture

CLI input
↓
src/index.ts — reads candidate name
↓
src/agent.ts — orchestrates 4 steps
↓
src/stackone.ts — MCP client
↓
api.stackone.com/mcp
↓ ↓ ↓
BambooHR Notion Slack
↓
audit-log.json

Built in TypeScript. 9 files. Clean structure.
Supports multiple candidates in one command:

npm run onboard -- john sarah alex priya

Tech Stack

Language → TypeScript
Runtime → Node.js + tsx
Gateway → StackOne MCP server
HRIS → BambooHR
Docs → Notion
Messaging → Slack
Audit → JSON file

3 Real Errors I Hit

These taught me the most about StackOne MCP.

─────────────────────────────────────────
Error 1 — Missing Accept Header

Not Acceptable: Client must accept both
application/json and text/event-stream

Why: StackOne MCP uses streaming protocol.
Must declare support for both formats.

Fix: Add this header to every request:

"Accept": "application/json, text/event-stream"
─────────────────────────────────────────
Error 2 — Silent BambooHR Redirect

No error thrown. Agent said success.
Employee never appeared in BambooHR.

The response was returning:
"location": "https://www.bamboohr.com"

Instead of:
"location": "https://api.bamboohr.com/
.../mytestorg/.../employees/115"

Why: Wrong BambooHR account connected
in StackOne. Requests went to wrong instance.

Fix: Delete wrong account in StackOne.
Re-link with correct subdomain: mytestorg.
─────────────────────────────────────────
Error 3 — Wrong Slack Tool Name

MCP error -32602: Tool slack_post_message
not found

Why: StackOne names tools differently
from the underlying provider APIs.

Fix: Called tools/list to see all Slack tools.
Correct name was slack_send_message.
Field name was channel_id not channel.

Pro tip: Always use tools/list before
assuming tool names. Saves hours of guessing.
─────────────────────────────────────────
What I Learned About StackOne MCP

Always accept text/event-stream in headers.
Each integration has its own Account ID.
Use tools/list to find exact tool names.
All tools wrap fields inside body object.
Wrong account = silent redirect, not error.
StackOne Logs shows every API call made.

Results

BambooHR → Employee #115 created ✓
Notion → Onboarding page with Day 1 checklist ✓
Slack → Welcome message in #onboarding-alerts ✓
Audit → 4 timestamped entries logged ✓

Final Thought

StackOne MCP made connecting to 4 enterprise
platforms easier than connecting to one platform
the traditional way.

One API key replaced four SDKs.
One endpoint replaced four auth systems.
One integration replaced months of work.

Full code on GitHub:
github.com/prathyushak828/stackone-onboarding-agent

If you are building AI agents that need to touch
enterprise SaaS — StackOne MCP is worth your time.

StackOne #MCP #TypeScript #AIAgents #BuildInPublic

Forem: prathyusha k

I build an AI agent using StackOne MCP

StackOne #MCP #TypeScript #AIAgents #BuildInPublic