Explanation of orra plan engine vs MCP. (#226)

Author: ezodude

README.md

@@ -36,7 +36,8 @@ By intelligently coordinating tasks across your agents, tools, and existing stac
 
 - [Installation](#installation)
 - [How The Plan Engine Works](#how-the-plan-engine-works)
-- [How orra Compares](#how-orra-compares)
+- [Orra vs Agent Frameworks & Workflow Engines](#orra-vs-agent-frameworks-and-workflow-engines)
+- [Orra Plan Engine vs MCP](#orra-plan-engine-vs-mcp)
 - [Guides](#guides)
 - [Explore Examples](#explore-examples)
 - [Docs](#docs)
@@ -244,7 +245,7 @@ The Plan Engine ensures:
 * Real-time status updates
 * Webhook events for result delivery and monitoring
 
-## How orra compares
+## Orra vs Agent Frameworks and Workflow Engines
 
 Orra takes a unique approach to AI workflow orchestration. Here's how it compares to other solutions:
 
@@ -258,6 +259,35 @@ Orra takes a unique approach to AI workflow orchestration. Here's how it compare
 
 Orra is for building AI systems that need to adapt and recover when things go wrong, without brittle scripts or manual fixes.
 
+## Orra Plan Engine vs MCP
+
+| Aspect | Orra Plan Engine                                          | Model Context Protocol (MCP)                         |
+|--------|-----------------------------------------------------------|------------------------------------------------------|
+| **Purpose** | Orchestrate multi-agent workflows end-to-end              | Connect single LLM to external tools/data            |
+| **Best For** | Production multi-agent applications that need reliability | Extending LLM capabilities with APIs and databases   |
+| **Planning** | AI dynamically generates execution plans                  | Developer defines available tools                    |
+| **Execution** | Stateful workflow coordination with recovery              | Direct tool calls via LLM                            |
+| **State Management** | Persistent orchestration state with audit logs            | Stateless request/response                           |
+| **Error Handling** | Automatic retries, compensation, and rollback             | Tool returns error to LLM                            |
+| **Complexity** | Full workflow orchestration platform                      | Simple integration protocol                          |
+| **When to Use** | Building production AI systems with multiple agents       | Building AI assistants, enhancing single agents      |
+
+### Real-World Examples
+
+**Use MCP when:**
+- Adding web search to your Claude chatbot
+- Connecting an LLM to your company's database
+- Building a research assistant that needs multiple data sources
+
+**Use Orra when:**
+- Orchestrating fraud detection agent pipelines without writing custom abort/retry logic or state management
+- Building incident response agent workflows without implementing failure recovery or escalation infrastructure
+- Creating e-commerce agent workflows without building compensation logic or transaction coordination
+
+### Can They Work Together?
+
+Yes! MCP handles the "how do I connect to systems" while orra handles the "how do I coordinate complex workflows." You might use MCP to expose individual agent capabilities, then use Orra to orchestrate those agents in production workflows.
+
 ## Guides
 
 - [From Fragile to Production-Ready Multi-Agent App](https://github.com/orra-dev/agent-fragile-to-prod-guide)