Credential Application and LLM Tool Generation

With request encoding complete, we added the authentication layer and started generating native LLM tools from OpenAPI operations.

Security Scheme Binding

Credentials apply to requests based on declared security requirements. An operation requiring OAuth gets a Bearer token; one requiring API key gets the key in its declared location (header, query, or cookie). The security scheme type determines how credentials transform into request headers or parameters.

Scheme-Bound Isolation

A credential is bound to a security scheme by name. The execution engine only applies it to operations that explicitly declare that scheme. Even with valid credentials, they cannot leak to operations that don’t request them. This is a structural guarantee, not a policy.

Server URL Templating

Server URL templates support variables with enum constraints. Variable schema generation enables validation. Server override at template creation or request encoding time supports multi-environment specifications.

LLM Tool Generation

Tool generator transforms OpenAPI operations into native LLM tool definitions. Takes an operation’s parameters and request body, generates a JSON Schema for function calling, registers tools dynamically.

Schema Normalization

LLM vendors each implement an unspecified subset of JSON Schema for function calling. No vendor documents which keywords they support. No two vendors support the same subset. additionalProperties works in some contexts but not others. oneOf supported by one vendor, silently ignored by another. Nested $ref resolution varies.

We’re building normalizers to transform schemas into each vendor’s accepted subset. Every hundred operations in our corpus surfaces another valid construct that some vendor rejects.

Authentication Header Normalization

Analysis of 4,138 OpenAPI specifications from the APIs Guru corpus revealed that only 39% properly declare security schemes. The remaining 61% use direct header parameters, creating challenges for generic clients and AI agents that need clean security boundaries.

Among APIs using direct auth headers, 62% use the generic Authorization header. Pattern analysis shows predictable distribution: 66% are Bearer tokens (detectable via “bearer”, “jwt”, or “token” in descriptions), 32% are OAuth 1.0 signatures, and only 3% are ambiguous. Description-based detection is sufficient.

The normalizer detects common auth headers—Authorization, X-Api-Key, Auth-Token, Access-Token, and variants—and converts them to proper security schemes. Type inference uses parameter descriptions. Merge strategies control how normalized schemes inject into operations: always, when-missing, or when-undeclared.