Difference between revisions of "Model Context Protocol"
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| + | ===Difference between RAG & MCP=== | ||
| + | The difference between RAG (Retrieval-Augmented Generation) and MCP (Model Context Protocol) lies in their approach to data retrieval and usage in AI systems: | ||
| + | * RAG (Retrieval-Augmented Generation): | ||
| + | ** RAG fetches external data in real-time to augment the AI's responses. For example, it might query a database or API to retrieve the latest information before generating an answer. | ||
| + | ** It is highly flexible, allowing AI to access diverse sources for context-specific queries. However, it can be resource-intensive, as each query requires external connections. | ||
| + | * MCP (Model Context Protocol): | ||
| + | ** MCP focuses on maintaining context within the AI itself, enabling it to remember previous interactions and provide personalized responses. | ||
| + | ** It reduces the need for external data retrieval, relying on stored memory and predefined prompts. | ||
| + | ** MCP is more efficient for workflows requiring continuity and real-time data integration. | ||
| + | In essence, RAG is like fetching fresh data for every query, while MCP is about leveraging stored context for smarter, seamless interactions | ||
==References== | ==References== | ||
<references /> | <references /> | ||
Revision as of 12:35, 9 April 2025
Contents
Full Title or Meme
Context
Quantum computers are expected to break traditional cryptographic systems like RSA and ECC. In response,
MCP is a security nightmare!
Don’t get me wrong — at Wexa, we see Model Context Protocol as the HTTP of the GenAI era. It’s the missing link to make AI assistants truly agentic and interoperable.
Problems
MCP doesn’t govern security by default. -> Tool poisoning attacks are a cakewalk if you’re not explicitly validating or sanitizing inputs. Anyone can sneak in malicious instructions through tool descriptions or context — and the model will just obey.
Versioning is a mess. -> There’s no clear standard for how models or tools should handle different MCP versions. That means you risk breaking tools silently — or worse, running outdated logic with no warning.
Persistent context = persistent risk. -> If your AI coworker remembers things across sessions, what happens when the context itself is compromised or manipulated?
We’re bullish on MCP — it’s foundational to how we’re building secure, scalable AI agents inside Wexa.
if you’re using MCP in production today, you’re likely exposed unless you’ve already wrapped it in a tight security layer.
MCP is powerful. But don’t assume it’s safe out of the box.
Solutions
Xinyi Hou, Yanjie Zhao, Shenao Wang, Haoyu Wang Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions 2025-03-30 https://arxiv.org/abs/2503.23278
Enable AI Agent
Difference between RAG & MCP
The difference between RAG (Retrieval-Augmented Generation) and MCP (Model Context Protocol) lies in their approach to data retrieval and usage in AI systems:
- RAG (Retrieval-Augmented Generation):
- RAG fetches external data in real-time to augment the AI's responses. For example, it might query a database or API to retrieve the latest information before generating an answer.
- It is highly flexible, allowing AI to access diverse sources for context-specific queries. However, it can be resource-intensive, as each query requires external connections.
- MCP (Model Context Protocol):
- MCP focuses on maintaining context within the AI itself, enabling it to remember previous interactions and provide personalized responses.
- It reduces the need for external data retrieval, relying on stored memory and predefined prompts.
- MCP is more efficient for workflows requiring continuity and real-time data integration.
In essence, RAG is like fetching fresh data for every query, while MCP is about leveraging stored context for smarter, seamless interactions
