No manual wrappers
Import a Swagger/OpenAPI URL and generate MCP-compatible tools from operation metadata instead of writing a custom server per API.
OpenAPI to MCP
Convert Swagger and OpenAPI specs into MCP tools
Swagger to MCP Gateway turns existing REST API operations into a curated Model Context Protocol tool catalog. Publish safe endpoints, keep upstream credentials server-side, and monitor AI-driven tool traffic without building custom adapters.
SwaggerOpenAPIREST APIMCP serverAI agents
app.swaggertomcp.com/publish
Swagger to MCP
OpenAPI to MCP publish flow
Import OpenAPI source
https://api.example.com/openapi.json
Generated tools
18 selectedget_order_by_id
GET /orders/{id}
create_support_ticket
POST /tickets
search_customers
GET /customers/search
MCP endpoint
/mcp/acme-orders
Claude, Cursor, VS Code, or Gateway Chat can discover the selected API tools.
Auth policyServer-side
LogsRedacted
Why it matters
A production boundary for API tools
Hand-written MCP adapters are quick to start but easy to outgrow. The Gateway centralizes tool generation, auth, usage controls, and observability.
LLM-friendly descriptions
Override tool descriptions so Claude, Cursor, and other MCP clients can choose the right operation and pass better arguments.
Redacted logs
Track tool calls, latency, success rates, and failure details while masking sensitive request and response values.
Use cases
Connect existing REST APIs to AI workflows
Use OpenAPI to MCP when your application already exposes HTTP APIs and you need a safer AI-facing tool layer.
Internal operations APIs
Expose selected service, ticketing, order, or support actions to AI assistants without leaking broad API credentials.
Customer-facing SaaS APIs
Ship a controllable MCP endpoint for a product API while retaining quota, plan, and tool-level governance.
Developer demos
Turn public OpenAPI specs into working MCP surfaces for prototypes, evaluations, and agent demos.
Workflow
From source to MCP endpoint
The Gateway keeps source discovery, publishing, execution, and monitoring separated so the AI-facing surface stays controlled.
Step 1
Import the OpenAPI source
Provide a Swagger/OpenAPI JSON or YAML URL. The Gateway resolves operation metadata and base URL behavior.
Step 2
Review generated tools
Inspect the generated tool list, hide unsafe operations, and improve descriptions before publishing.
Step 3
Connect the MCP endpoint
Use the generated MCP URL with Claude, Cursor, VS Code, or any compatible MCP client.
FAQ
Common questions
Short answers for teams comparing MCP adapters, API gateways, and database access for AI agents.
Is this an OpenAPI generator or an MCP gateway?
It is both for the OpenAPI flow. The Gateway reads OpenAPI metadata, publishes MCP tools, enforces account limits, and proxies validated tool calls to the upstream REST API.
Do AI clients need my upstream API key?
No. In the recommended mode, clients authenticate to the Gateway and the Gateway injects encrypted upstream credentials server-side.
Can I choose which endpoints become tools?
Yes. Generated tools can be published or hidden individually, and their descriptions can be customized for better model behavior.
Are both Swagger and OpenAPI supported?
Yes. The OpenAPI flow accepts Swagger/OpenAPI JSON or YAML URLs and uses the document metadata to create operation-derived MCP tools.
Does every endpoint automatically become a published MCP tool?
No. The Gateway can generate tools from OpenAPI operations, but the published surface is curated. You can hide unsafe or unnecessary operations before using the MCP endpoint.
Can tool descriptions be edited for agent-ready behavior?
Yes. Tool descriptions can be customized so the MCP catalog is more agent-ready. Clear descriptions help Claude, Cursor, VS Code, and other MCP clients choose the correct operation and pass better arguments.
What happens if the OpenAPI spec changes?
The Gateway reads the OpenAPI document during the publish/import flow and stores generated tools for the integration. When the upstream spec changes, review and republish or update the integration so the MCP surface reflects the intended operations and descriptions.
Can this be used with public and internal APIs?
Yes. Public APIs can be used for demos and prototypes, while internal APIs can be published behind Gateway authentication so AI clients do not receive broad upstream credentials.
Do OpenAPI tool calls go directly from the AI client to my API?
No. MCP clients call the Gateway MCP endpoint. The Gateway checks integration state, account limits, publication state, credential policy, and logging rules before forwarding the request to the upstream REST API.