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atlas-stream-processing

Provision and manage MongoDB Atlas Stream Processing workspaces, connections, and processors.

Updated Aug 27, 2026
Search Tags:#automation#aws#kafka#mongodb#pipelines#atlas#stream-processing
One-click install
npx skills add https://github.com/jeremylasne92-hue/siteweb2 --skill atlas-stream-processing
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: atlas-stream-processing
Source: https://github.com/jeremylasne92-hue/siteweb2/tree/main/.agents/skills/atlas-stream-processing
Command: npx skills add https://github.com/jeremylasne92-hue/siteweb2 --skill atlas-stream-processing

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill automates the end‑to‑end management of MongoDB Atlas Stream Processing workflows, eliminating the need for manual API calls to provision workspaces, configure data sources and sinks, and control processor lifecycles.

Core Features & Use Cases

  • Workspace provisioning – create and configure ASP workspaces with appropriate tier and region settings.
  • Connection management – set up and validate Kafka, Atlas clusters, S3, HTTPS, and Lambda connections for both source and sink roles.
  • Processor lifecycle – build, start, stop, modify, and safely teardown processors with built‑in diagnostics and tier‑sizing recommendations.
  • Use case example – Build a real‑time fraud detection pipeline that reads from a Kafka topic, applies tumbling‑window aggregation, and writes alerts to an Atlas collection.

Quick Start

Create a new workspace, add a Kafka connection, build a simple $source‑$merge processor, and start it.

Frequently Asked Questions about atlas-stream-processing

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate MongoDB Atlas Stream Processing pipeline provisioning?▼

Automate Atlas Stream Processing pipelines by provisioning workspaces, configuring Kafka or S3 connections, and managing processor lifecycles without manual API calls. This eliminates manual configuration for streaming data ingestion and output routing.

Can I build a Kafka to MongoDB Atlas streaming data pipeline?▼

Yes, Kafka to MongoDB Atlas streaming pipelines are supported by configuring Kafka as a source connection and Atlas collections as a sink. You can apply transformations like tumbling-window aggregations before writing data to Atlas collections.

What connections does Atlas Stream Processing support for data sources and sinks?▼

Atlas Stream Processing supports Kafka, Atlas clusters, S3, HTTPS, and Lambda connections for both source and sink roles. You can ingest from these sources and output to Atlas collections, Kafka topics, or S3 buckets.

Do I need a MongoDB MCP Server to manage Atlas Stream Processing?▼

Yes, a MongoDB MCP Server configured with Atlas API credentials is required to authenticate and manage Atlas Stream Processing. This server acts as the interface for provisioning workspaces and controlling processor lifecycles.

How do I safely teardown and debug an Atlas Stream Processing processor?▼

Safely teardown Atlas Stream Processing processors using built-in diagnostics and safe teardown operations. The system provides debugging diagnostics and tier-sizing recommendations to help identify issues before removing processors.

What's the best way to size tiers for Atlas Stream Processing workspaces?▼

Atlas Stream Processing provides built-in tier-sizing recommendations when creating and modifying workspaces and processors. These recommendations help you select appropriate tiers and regions based on your streaming data pipeline requirements.

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