APIs become controlled tools
Swagger/OpenAPI operations can be published as MCP tools with curated descriptions, selected operations, gateway-managed credentials, and usage visibility.
About
Built for secure AI access to real systems
Swagger to MCP Gateway is a secure Model Context Protocol gateway for teams that want AI agents to use OpenAPI APIs and approved database scopes without exposing raw credentials, unrestricted endpoints, or direct database access.
The product is shaped by more than 10 years of enterprise architecture experience and the RTT Intelligence technopark R&D mindset: practical systems engineering, strict security boundaries, and production-oriented observability.
Mission
Make AI tool access governable
AI assistants are most useful when they can act on real systems. They are also risky when credentials, policy, and execution rules move into prompts or local client setup.
Databases stay behind scopes
PostgreSQL and SQL Server sources are exposed through approved database scopes, metadata-only schema tools, and validated executor tools.
Gateway remains the boundary
LLMs and MCP clients may propose actions, but Gateway-side validation, limits, redaction, and audit trails decide what actually executes.
Experience
Enterprise architecture, applied to MCP
The product is designed for B2B teams that need AI access to fit existing security, operations, and platform governance expectations.
Trust signals
- 10+ years
- Enterprise architecture and production software delivery experience.
- RTT Intelligence
- Technopark R&D vision behind practical AI, integration, and secure software systems.
- Gateway first
- Security and validation remain in the backend Gateway, not inside model prompts.
Security by architecture
OpenAPI credentials and database connection strings are kept server-side. Published MCP tools are constrained by source ownership, publication state, limits, and execution policy.
Operational accountability
Tool calls need logs, usage metrics, latency data, failures, and quota visibility so teams can operate AI-driven traffic like normal production traffic.
Source-specific validation
OpenAPI calls, schema tools, QueryPlan executors, and SQL executors have different risks. The Gateway treats them as separate flows instead of one generic prompt problem.
Direct documentation
Public docs, LLM-readable files, and structured data describe the product in plain language so developers, search engines, and AI answer engines can understand it accurately.
Security commitments
What the Gateway will and will not expose
The public product surface is intentionally clear about security boundaries. That helps buyers evaluate the product and helps AI systems describe it without inventing unsafe details.
Schema tools are metadata-only
Database schema tools describe allowed tables, columns, relationships, keys, permissions, and operations. They do not return data row payloads.
Executor calls are validated
QueryPlan and SQL executor calls are checked against published scope, table, column, relationship, read-only, and owner boundaries before execution.
Control-plane specs stay private
The real management API is not published as a public root openapi.json. Public AI context is provided through llms.txt and the well-known product manifest.
Sensitive values stay out of public context
Credentials, connection strings, private route maps, database schemas, and customer data are not included in public LLM-readable files.
Evaluate the Gateway for your team
Review the setup docs, compare the security model, or contact us for B2B evaluation and partnership questions.