---
title: "Scaling AI Agent Fleets with Model Context Protocol — WhatsMCP Blog"
description: "An architectural walkthrough on exposing WhatsApp thread history and tools natively to Claude and custom agent runtimes securely."
url: "https://whatsmcp.com/blog/scaling-ai-agent-fleets-with-mcp"
---

An architectural walkthrough on exposing WhatsApp thread history and tools natively to Claude and custom agent runtimes securely.

## Why Thread History Is the Hard Part

Most MCP integrations start with tool calls and treat conversation state as an afterthought. For a WhatsApp agent that's backwards: one that can send a message but can't see the last twenty exchanges in a thread will re-ask questions a human already answered. Every read path is scoped to a single API key's own accounts from the first line of the handler, not filtered after the fact.

## Cursor-Based Polling, Not Webhooks-Only

Agent runtimes reconnect, restart, and occasionally crash mid-session. A push-only design loses whatever arrived while the runtime was down. Every message-list call instead returns a cursor, and an agent — or its host runtime — resumes from exactly where it left off:

- No gap and no duplicate delivery, even for two messages that land in the same millisecond.
- A crashed runtime catches up by replaying from its last known cursor instead of missing a window of history.
- Webhooks remain available as a push hint, but the cursor is the source of truth an agent can always fall back to.

> **Technical note:** an agent runtime that never persists its cursor re-reads from the beginning on every restart. Persist it, or accept the replay cost.

## What We'd Do Differently

We under-documented the persistence requirement in the first release of the tool surface, and it is the single most common support question fleet operators ask.