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atlas-stream-processing

Manage MongoDB Atlas Stream Processing pipelines, connections, and processors.

4|2|Updated May 18, 2022
Search Tags:#mcp#pipeline#kafka#mongodb#atlas#dlq#stream-processing
One-click install
npx skills add https://github.com/pjmagee/starwars-data --skill atlas-stream-processing-pjmagee
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: atlas-stream-processing
Source: https://github.com/pjmagee/starwars-data/tree/main/.agents/skills/atlas-stream-processing
Command: npx skills add https://github.com/pjmagee/starwars-data --skill atlas-stream-processing-pjmagee

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Provides a complete, guarded workflow for building, operating, and troubleshooting MongoDB Atlas Stream Processing pipelines so teams avoid misconfiguration, unintended billing, and data loss. It consolidates workspace provisioning, connection creation (Kafka, Atlas cluster, S3, HTTPS, Lambda, Schema Registry), processor lifecycle operations, diagnostics, and safe teardown under MCP tool orchestration and pre-deploy validation.

Core Features & Use Cases

  • Provision & Build: Create workspaces, register connections, and build processors with prescribed field mappings and elicitation for sensitive data.
  • Lifecycle Management: Start, stop, modify, and teardown processors with state checks, safety confirmations, and cascading-delete protections.
  • Debugging & Diagnostics: Guided diagnostic patterns, diagnose-processor usage, DLQ inspection, and concrete ordered remediation steps for common failures (Kafka partitions, OOM, schema errors).
  • Sizing & Cost Control: Tier recommendation heuristics, parallelism calculations, and pre-start billing warnings to avoid unexpected charges.
  • Use Case: Deploy a Kafka→window→Atlas rollup pipeline with DLQ and monitoring, or diagnose a FAILED processor caused by a misconfigured connection and recover safely.

Quick Start

Create a workspace, add and inspect connections for your sources and sinks, validate fields via search-knowledge, then build and start a processor with a DLQ configured using the MongoDB MCP Server.

Frequently Asked Questions about atlas-stream-processing

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

FAQPage Schema
How do I manage MongoDB Atlas Stream Processing pipelines end to end?▼

You can manage MongoDB Atlas Stream Processing pipelines by provisioning workspaces, registering Kafka or S3 connections, building processors with field mappings, and handling lifecycle operations like start, stop, and teardown through orchestrated tooling.

How do I diagnose a failed Atlas Stream Processing processor?▼

Diagnose a failed Atlas Stream Processing processor by running guided diagnostic patterns, inspecting the DLQ for dropped records, and following ordered remediation steps for common failures like Kafka partition misconfigurations, OOM errors, or schema validation issues.

Can I create Kafka and S3 connections for Atlas Stream Processing?▼

Yes, you can create connections for Kafka, Atlas clusters, S3, HTTPS, Lambda, and Schema Registry within your Atlas project. The workflow enforces pre-deploy connection inspection and search-knowledge validation to prevent misconfiguration and data loss.

How do I avoid unexpected billing when starting an Atlas Stream Processing pipeline?▼

To avoid unexpected billing when starting an Atlas Stream Processing pipeline, use the tier recommendation heuristics and parallelism calculations. The workflow triggers pre-start billing warnings and explicit user confirmations before provisioning or modifying resources.

How do I safely tear down an Atlas Stream Processing workspace and its processors?▼

Safely tear down an Atlas Stream Processing workspace by executing teardown workflows with state checks, safety confirmations, and cascading-delete protections. This prevents unintended data loss when removing processors and associated connection resources.

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

Yes, configuring Atlas Stream Processing requires a MongoDB MCP Server with Atlas API credentials. The server orchestrates tool calls to enforce pre-deploy validation, DLQ configuration, and explicit confirmations for destructive actions.

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