What Is MCP and How Catalyst Helps
What Is the Model Context Protocol?
The Model Context Protocol (MCP) is an open standard introduced by Anthropic that defines how AI agents connect to external tools and data sources. Instead of building custom integrations for every service an agent needs, developers expose capabilities through MCP servers and connect to them through MCP clients, using a single, model-agnostic protocol.
With open-source libraries available in Python, TypeScript, Java, C#, Go, and more, alongside a rapidly growing ecosystem of thousands of MCP servers, MCP is becoming the de facto standard for how agents and tools integrate. Recognized as a foundational project by the Agentic AI Foundation (AAIF), MCP is now the common language that agent frameworks, tool providers, and enterprises are converging on for AI-to-system connectivity.
Benefits of MCP
- Standardized integration: MCP replaces fragmented, per-service integrations with a single protocol. An agent built against MCP can connect to any compliant server without custom adapter code.
- Dynamic tool discovery: Agents discover available tools at runtime rather than compile time, enabling flexible architectures where servers can be added, updated, or removed without redeploying clients.
- Model-agnostic: MCP works across LLM providers and agent frameworks. The same MCP server can serve agents built with LangGraph, CrewAI, Dapr Agents, or other frameworks.
- Separation of concerns: Tool logic lives in MCP servers, while agent logic lives in clients. Teams can develop, deploy, and scale each side independently.
Production Challenges with MCP
MCP helps standardize how agents connect to tools, but many production concerns still need to be handled outside the protocol. As teams move from experimentation to production use, they often need additional capabilities for authentication, authorization, downstream governance, reliability, observability, and operations.
| Challenge | Impact |
|---|---|
| Authentication needs to be handled by the deployment environment | Teams often need additional infrastructure to validate caller identity and reject unauthenticated requests before they reach MCP servers. |
| Authorization is not universally enforced across environments | MCP does not provide a universal model for enforcing fine-grained authorization across agents, servers, and tools. Additional controls are often needed to determine which clients can access which capabilities. |
| Downstream access governance is outside MCP | When an MCP server calls another service, such as a database, an API, or another MCP server, access control for that hop is typically handled outside the protocol. Without additional controls, outbound access can be harder to manage consistently. |
| Reliability for downstream calls is not built into MCP | Retries, timeout policies, circuit breaking, and other resiliency features for downstream service calls generally need to come from the application or platform layer. Without them, transient failures can be harder to contain. |
| End-to-end observability is not standardized | Teams often need additional tracing, logging, and monitoring to understand request flows across agents, MCP servers, and downstream services. Troubleshooting multi-step tool interactions can otherwise be difficult. |
| Operational concerns are left to the platform | Capabilities such as transport security, secret management, rate limiting, and service discovery are typically handled outside MCP. As the number of MCP servers grows, managing these concerns consistently can add operational overhead. |
How Catalyst Addresses These Challenges
Catalyst provides MCP gateway capabilities for authentication, authorization, resiliency, and downstream policy enforcement, while preserving a distributed architecture rather than introducing a standalone gateway.
| Challenge | Catalyst Solution |
|---|---|
| Authentication needs to be handled by the deployment environment | Bearer middleware validates JWT tokens in the HTTP pipeline before requests reach application code. This lets you protect MCP endpoints with standard OAuth2 and OIDC providers. |
| Authorization is not universally enforced across environments | Access policies assign application identities and enforce allow or deny rules per caller. Requests that do not match policy can be rejected before they reach the target service. |
| Downstream access governance is outside MCP | Granular policies can be applied independently at each service boundary. An MCP server can be allowed to call one backend while being restricted from reaching another. |
| Reliability for downstream calls is not built into MCP | Resiliency policies provide configurable timeouts, retries with exponential backoff, and circuit breakers to help contain failures from slow or unhealthy downstream services. |
| End-to-end observability is not standardized | Built-in observability integrates with logs, metrics, and tracing backends, while the Catalyst dashboard provides visibility into application identities, invocation flows, and policy enforcement across services. |
| Operational concerns are left to the platform | Catalyst handles mTLS, certificate rotation, service discovery, and middleware configuration centrally, reducing per-endpoint wiring and helping teams manage MCP deployments more consistently. |
MCP server code does not need to import Catalyst or Dapr. Catalyst works with any MCP framework, any language, and any deployment target, including air-gapped environments.
Get Started
Try these tutorials to secure an MCP server with Catalyst: