UTCP vs MCP: A Comparison

This page compares the Universal Tool Calling Protocol (UTCP) with the Model Context Protocol (MCP), highlighting their different approaches to agent-tool integration.

Video Overview

Architectural Differences

Aspect	MCP	UTCP
Core Model	Middleman	Manual
Architecture	Agents ↔ MCP Server ↔ Tool	Agent ↔ Tool (Direct)
Integration Approach	Wraps existing tools	Describes how to call existing tools
Network Hops	Double (Agent → MCP → Tool)	Single (Agent → Tool)
Protocol Dependency	Hard dependency on protocol for every call	Protocol only needed during discovery

The Middleman vs Manual Philosophies

The MCP "Middleman" Approach

MCP positions itself as the "USB-C for AI Agents" — a universal adapter that all tools must plug into. This approach:

• Forces all traffic through a new protocol layer
• Requires writing "wrappers" for existing tools
• Needs to reinvent solutions for auth, security, and other infrastructure concerns

This creates what we call the "wrapper tax": the additional infrastructure, development, and maintenance overhead required to adapt existing tools to work with MCP.

The UTCP "Manual" Approach

UTCP takes a different approach — it's a "manual" that describes how to call tools directly:

• Provides all necessary information to call native APIs directly
• Gets out of the way after tool discovery
• Leverages existing infrastructure for auth, security, etc.

This eliminates the wrapper tax and allows organizations to expose their existing APIs to AI agents without building and maintaining additional infrastructure.

Feature Comparison

Feature	MCP	UTCP
Tool Discovery	Via MCP Server	Via provider's discovery endpoint
Protocol Support	HTTP Streaming	HTTP, WebSockets, gRPC, CLI, etc.
Authentication	Handled by MCP Server	Uses tool's native authentication
Streaming	Native support	Supported via appropriate providers (SSE, WebSockets)
Implementation Complexity	High (requires wrapper servers)	Low (simple JSON definitions)
Performance	Additional overhead due to proxy	Direct, native performance
Evolution Speed	Slow (all participants must update)	Fast (individual providers can evolve independently)

When to Choose Each Protocol

Choose MCP When:

• You need strict standardization across all tools
• You're building a closed ecosystem where you control all components
• You're willing to invest in building and maintaining wrapper servers

Choose UTCP When:

• You want to leverage existing APIs without building wrappers
• You need to support diverse communication protocols
• You value direct, efficient communication
• You prioritize low implementation overhead
• You want to minimize infrastructure costs

Real-World Example

Consider an organization with an existing REST API that they want to expose to AI agents:

With MCP:

1. Build an MCP server that wraps the REST API
2. Translate all calls between MCP format and REST format
3. Maintain and scale this additional server infrastructure
4. Handle authentication translation between MCP and the API

With UTCP:

1. Create a simple JSON definition describing the REST API
2. Expose this definition via a discovery endpoint (typically /utcp)
3. The AI agent can now call the REST API directly

Code comparison

You can find a full typescript example detailing the MCP and UTCP approach here.

Conclusion

Both MCP and UTCP aim to solve the problem of standardizing tool calling for AI agents, but they take fundamentally different approaches.

MCP acts as a middleman, requiring all tools to be wrapped in its protocol. This provides standardization but at the cost of additional infrastructure and development overhead.

UTCP acts as a manual, describing how to call tools directly using their native interfaces. This eliminates the wrapper tax and leverages existing infrastructure, at the cost of requiring clients to handle different communication protocols.

The choice between them depends on your specific requirements, existing infrastructure, and development resources. However, UTCP's "manual" approach offers significant advantages in terms of simplicity, efficiency, and leveraging existing investments in API infrastructure.