MCP vs Skills Debate: Understanding the Roles and the Real Problem of Context Rot

MCP vs Skills: Different Roles for AI Agents

A recent discussion on r/openclaw addresses claims that "MCP is dead" because Skills have replaced it. The author clarifies these are two distinct components with different functions.

What Skills Are

• Skills are prompts - "really good, reusable prompts"
• Sometimes bundled with scripts and examples
• They tell an agent: "here's how you should behave when doing X"

What MCP Provides

• MCP is "plumbing" - infrastructure for agents
• Gives agents tools and authentication
• Provides context steering (often overlooked)
• Responses from MCP tools don't just return data - they guide the agent on what to do next

The Relationship Between Them

The author argues both are necessary: "A skill without tools is a well-written instruction manual with no hands. A tool without a skill is raw power with no direction."

The Real Problem: Context Rot

More concerning than the MCP vs Skills debate is the issue of context rot:

• Agents forget instructions over time
• Skills get buried deep in the context window and get ignored
• Tools pile up and overwhelm the agent's attention
• The author has observed: "I've seen agents explicitly instructed to use a specific skill and most of the time, they just skip it entirely."

The Future Architecture

The author suggests the future isn't skills OR MCP, but rather: "skills + tools + isolated context (subagents) working together." This is why they're building Bindu as "an operating layer for agents because once you solve the behavior and tooling question, you still need identity, communication, and payments to make agents actually work together in production."

The post concludes that while "MCP is dead" makes for good engagement, "the agents that ship? They use everything."