What if your internal APIs could talk to AI agents without manual integration, schema rewrites, or hallucination-prone trial and error?
Now they can.
We’re excited to introduce a powerful new feature in Gentoro that makes it easier than ever to connect your APIs to the world of intelligent agents and agentic workflows—without writing a single line of integration code.
Widely used public service? Yes. Private internal API? Absolutely. With this release, Gentoro can now take any OpenAPI specification and automatically generate a complete set of Model Context Protocol (MCP)-compliant tools based on that spec. The tools are optimized for LLMs and immediately usable by any agent or framework that supports MCP, including Claude Desktop, Cursor.ai, Goose, LangChain, the OpenAI SDK, and more.
From OpenAPI Spec to Agentic Tools, in Minutes
Most APIs weren’t designed with LLMs or AI agents in mind. APIs often involve deeply nested structures, implicit assumptions, and machine-oriented schemas that language models struggle to interpret.
Gentoro reshapes these APIs into forms that better align with how agents interpret and use tools. More specifically, Gentoro:
- Ingests, parses, and enhances your API endpoints
- Abstracts complex parameters and structures
- Auto-generates user-aligned agentic tools that match how agents think
These agentic tools aren’t just raw endpoint wrappers. They’re ready-to-use, scalable, user-aligned connectors that allow AI agents to safely call your API.
Fewer Hallucinations, More Precision
LLMs are sensitive to nuance. A poorly named parameter or an ambiguous description can lead to hallucinations, misuse, errors, or endless retries.
That’s why Gentoro goes beyond basic OpenAPI fields, drawing on metadata, naming patterns, and natural language signals to produce clear, meaningful descriptions that help agents understand what each tool does and how to use it. Gentoro’s summarization pipeline generates:
- Rich, plain-language descriptions
- Parameter clarifications
- Tool usage guidance based on context, not just syntax
Structure and description quality reduces risk and directly improves agent performance. In a recent benchmark, Gentoro’s user-aligned agent tools executed 100% of prompts successfully, compared to 74% for optimized, API-aligned functions and just 33% with raw API mappings.
These performance evaluation results, documented in detail here, highlight the real-world value of aligning tools to how LLMs reason—not just how APIs are structured.
First-Class Support for Internal, Proprietary APIs
Unlike many agent tool platforms, Gentoro isn’t a cloud SaaS product. It runs inside your firewall. That means Gentoro lives where your systems already run, allowing you to generate tools from internal services, custom business logic, and proprietary APIs.
This is huge. It means your tools stay private. Your data stays local. And your agents can finally integrate with the systems that actually matter to your business.
The result? Deeper, more accurate integrations tailored to your real-world environment—not a watered-down simulation. No public proxy. No complex workarounds. With Gentoro, your agents can now work directly with the systems that matter most to your business.
Out-of-the-box MCP Compatibility
All tools generated by Gentoro are instantly compatible with the Model Context Protocol (MCP), the standard for connecting generative AI agents to external tools and systems.
MCP standardizes how AI models like Claude or GPT interact with tools, making it easier for agents to discover, understand, and use capabilities like “create ticket,” “fetch customer data,” or “post to Slack” without complex custom wiring.
For example, an MCP-compatible agent can query Gentoro’s tool server, interpret available functionality, and immediately begin executing tasks using those tools—no manual configuration required.
That means Gentoro-generated tools can be used immediately by:
- Claude Desktop – for local AI task automation
- Cursor.ai – for in-IDE coding and navigation
- Goose – for embedding autonomous workflows
- LangChain – for structured multi-step agent chains
- OpenAI SDK – for function-calling and tool use
- Custom-built MCP agents – in enterprise or OSS environments
By supporting MCP, Gentoro gives you a clean separation between agent logic and tool logic. You’re not locked into a single platform or vendor—and your tools remain interoperable across a growing ecosystem of LLM runtimes.
How It Works: Gentoro in Action
To begin, you create a new Toolbox in Gentoro and select the AI model you want to use (OpenAI, Claude, or any other supported provider). Then, you choose the OpenAPI connector and provide your API specification. This can be done by pasting a YAML or JSON file directly, or by linking to a hosted spec via URL.
If your API requires authentication, Gentoro supports common methods like OAuth, JWT, and API Keys, allowing you to securely define access.
Once submitted, Gentoro parses the API definition, enhances each endpoint with clear descriptions, and abstracts complex schemas into LLM-friendly formats. It then automatically generates a set of agentic tools, each mapped to a specific API function.
The tools are neatly organized by functional category, so it’s easy to find what you need. Each tool includes enhanced summaries, clarified parameters, and simplified input/output schemas to help LLMs reason more accurately.
You simply select the tools your agent will use and click Import. Gentoro then generates the underlying implementation code—secure, scalable, and ready to plug into your AI workflows. In just a few clicks, your internal API is transformed into an AI-accessible Toolbox, fully integrated with your agent ecosystem.
Figure 1: How Gentoro generates agentic tools from any OpenAPI spec
Coming Soon: Tool Builder for Customization (No Code Required)
Gentoro’s auto-generated tools are powerful by default, but we know one size doesn’t fit all. That’s why we’re launching Tool Builder, a natural-language interface for customizing, composing, and reshaping tools to fit your workflows.
With Tool Builder, you’ll be able to:
- Customize any generated tool (or create one from scratch) to match your unique workflows and domain needs
- Break tools down into modular components
- Combine multiple endpoints into a single composite tool
- Import and further refine third-party MCP tools
- Use simple, natural language to adjust parameters or reshape logic
Whether you’re streamlining repetitive tasks or orchestrating complex workflows, Tool Builder puts intuitive, flexible control in your hands. No code. No manual scripting. Just powerful tooling, designed by you and shaped by your goals.
Gentoro Turns APIs Into Intelligent Interfaces
Connecting LLMs to real systems isn’t just a technical challenge. In many cases, it’s the primary bottleneck to making AI actually useful in enterprise settings.
You can’t automate a workflow if your agents can’t talk to your tools. You can’t reduce manual overhead if your APIs are too complex for an LLM to reason about. And you can’t scale AI adoption if every integration requires dev resources and a custom wrapper.
With Gentoro, your internal APIs become intelligent agent interfaces in just a few clicks. No boilerplate, no guesswork… just Gentoro.
TLDR:
- Gentoro generates agent-ready tools from any OpenAPI-compliant spec
- Zero-code setup! Just drop in a spec and go
- Tools are user-aligned and optimized for LLM agent reasoning
- Enhanced descriptions reduce hallucinations and improve performance
- Gentoro runs inside your firewall for secure, private API access
- Supports proprietary, internal systems, not just public APIs
- Tools are MCP-compatible, instantly usable with Claude, Cursor, LangChain, OpenAI, Goose, and more
- Ideal for prototyping and scaling
- Tool Builder (coming soon) enables natural language customization, composition, and third-party tool integration—no code required
Next Steps
