ZuploZuplo
LoginStart for Free
  • Documentation
  • API Reference
Getting Started
    Develop in the portal
      1 - Setup Your Gateway2 - Rate Limiting3 - API Key Auth4 - Deploy5 - Dynamic Rate LimitingDynamic MCP Server - Quickstart
    Develop locally with the CLI
      1 - Setup Your Gateway2 - Rate Limiting3 - API Key Auth4 - Deploy5 - Dynamic Rate LimitingDynamic MCP Server - Quickstart
Concepts
    How Zuplo WorksRequest LifecycleProject StructureAuthenticationUpstream CredentialsAPI KeysAPI ErrorsRoutingPolicy FundamentalsOpenAPIEnvironmentsSource Control and DeploymentDevelopment OptionsAI GatewayMCP
API Management
AI Gateway
MCP Gateway
MCP Server
Developer Portal
Development
Deploying & Source Control
Analytics
Observability
Networking & Infrastructure
Account Management
Programming API
Build with AI
Zuplo CLI
Migration Guides
Platform LimitsVersion Support PolicySecuritySupportTrust & ComplianceChangelog
powered by Zudoku
Concepts

Model Context Protocol (MCP) Concepts

Model Context Protocol (MCP) is an open protocol that standardizes how AI applications — Claude Desktop, Claude Code, ChatGPT, Cursor, VS Code, and others — connect to external tools and data sources. Zuplo supports MCP in two directions, and this page explains both and when to use each.

Two ways to use MCP on Zuplo

FeatureWhat it doesWhen to use it
MCP GatewayProxies traffic to one or more upstream MCP servers. Handles OAuth, capability curation, and analytics.You want to expose existing MCP servers (Linear, Stripe, internal services, etc.) to AI clients through one endpoint.
MCP Server handlerTurns your OpenAPI routes into an MCP server. Each route becomes an MCP tool, prompt, or resource.You want to expose your own API as MCP so AI clients can call it as tools.

The two features solve different problems and can live in the same project.

MCP Gateway: one front door for upstream MCP servers

The MCP Gateway fronts one or more remote MCP servers with a single, OAuth-protected endpoint. Users sign in once through your identity provider, the gateway brokers credentials to each upstream server, and every tool call lands in your analytics — without raw tokens ever reaching the AI client. It solves five problems that appear as soon as a team uses more than a couple of MCP servers: discovery, authentication, authorization, observability, and guardrails. See How the MCP Gateway works.

MCP Server: turn your API into tools

The MCP Server handler transforms the routes in your Zuplo project into MCP tools, prompts, and resources that AI systems can discover and invoke. It uses your existing OpenAPI specifications for tool descriptions and composes with Zuplo's authentication, rate limiting, and audit logging policies.

How MCP fits into Zuplo

Neither MCP feature is a separate runtime. Both are sets of policies and route handlers that run inside the same Zuplo platform that runs your REST and GraphQL APIs — the same OpenAPI-as-config model, deployment pipeline, and observability primitives described in How Zuplo Works. MCP traffic flows through the same request lifecycle, so policies like rate limiting and audit logging apply to it the same way they apply to any other route.

Next steps

  • MCP Gateway quickstart — expose an upstream MCP server and connect Claude Desktop
  • MCP quickstart for the MCP Server handler — turn an API into MCP tools
  • Connect MCP clients — Claude, ChatGPT, Cursor, VS Code, and others
Edit this page
Last modified on August 28, 2026
AI GatewayOverview
On this page
  • Two ways to use MCP on Zuplo
    • MCP Gateway: one front door for upstream MCP servers
    • MCP Server: turn your API into tools
  • How MCP fits into Zuplo
  • Next steps