Provider-Agnostic Design

Provider-agnostic design is an architectural approach in which a tool or system functions independently of any specific AI model provider, working equally with Claude, OpenAI, LangChain, or any other agent framework without modification.

In Detail

The AI agent ecosystem is multi-provider. Organizations use Claude from Anthropic, GPT models from OpenAI, open-source models through LangChain, and increasingly mix providers within a single workflow. A tool designed for one specific provider creates lock-in: switching providers means rewriting integrations, retraining teams, and potentially losing functionality.

Provider-agnostic design avoids this problem by operating at the action level rather than the model level. Instead of integrating with a provider's specific API, SDK, or output format, a provider-agnostic tool interfaces with the universal operations that all agents perform — file reads, file writes, shell commands, and network requests. These action types are common across every agent framework, regardless of the underlying model.

Why Provider-Agnostic Matters

Avoiding lock-in. Organizations that choose security tools tied to a single provider face a difficult decision when they want to adopt a second provider or switch entirely. Provider-agnostic tools eliminate this friction.

Supporting multi-provider environments. Many teams run different agents for different tasks — Claude for code generation, an OpenAI model for data analysis, a LangChain pipeline for document processing. A provider-agnostic security layer applies consistent policies across all of them.

Future-proofing. The AI landscape evolves rapidly. New providers and frameworks emerge regularly. A provider-agnostic tool does not require updates for each new entrant; it works with any agent that performs standard action types.

Consistent security posture. Security gaps arise when different tools enforce different policies for different providers. A single provider-agnostic layer ensures that the same rules apply regardless of which model is driving the agent.

How Provider-Agnostic Is Achieved

Provider-agnostic design requires:

1. An action-level interface. The tool operates on actions (file_write, shell_exec, network) rather than on provider-specific constructs (tool_use blocks, function calls, completion formats).

1. No provider SDK dependencies. The tool does not import or depend on any provider's client library. It communicates through a universal protocol — typically a lightweight local API or middleware layer.

1. Configuration portability. Policies and rules are defined in terms of action types and targets, not in terms of provider-specific identifiers. A policy that denies shell_exec for rm -rf applies identically whether the action originates from Claude, OpenAI, or LangChain.

Provider-Specific vs. Provider-Agnostic

A provider-specific security tool might hook into OpenAI's function calling mechanism to intercept tool use. This works for OpenAI but requires a completely different integration for Claude's tool_use format and yet another for LangChain's agent executor. Each integration must be built, tested, and maintained independently.

A provider-agnostic tool sits below all of these provider-specific layers, intercepting the actual system operations the agent performs. The action is the same regardless of which provider generated it.

Examples

• A team uses Claude for coding tasks and an OpenAI model for research. A provider-agnostic security tool applies the same policy to both: file writes to ./src/ are allowed, shell commands are restricted to a safe list, and network requests require approval.

• An organization migrates from OpenAI to Claude. Because their security tool is provider-agnostic, no security configuration changes are needed. The same policies continue to apply.

• A developer builds a LangChain pipeline that orchestrates multiple model calls. The provider-agnostic security layer gates every action the pipeline produces, regardless of which model in the chain generated it.

Related Concepts

• Action-Level Gating — The mechanism that enables provider-agnostic security by operating at the action level.
• AI Agent Action Types — The universal action categories that form the provider-agnostic interface.
• Zero-Dependency Security — A complementary principle that avoids depending on provider SDKs.
• Policy Engine — The component that evaluates actions identically across providers.
• Deny-by-Default — The security posture applied uniformly regardless of provider.

In SafeClaw

SafeClaw, by Authensor, is provider-agnostic by design. It works with Claude, OpenAI, and LangChain agents without provider-specific configuration. SafeClaw operates at the action level — intercepting file_write, file_read, shell_exec, and network actions — which are common across all agent frameworks.

SafeClaw has zero third-party dependencies, meaning it does not import any provider SDK. Policies are defined in terms of action types and targets, not provider constructs. A policy configured for one provider applies identically to every other provider.

This design means that organizations running multi-provider agent environments can enforce a single, consistent security policy through SafeClaw. The 100% open source client (MIT license) is installable via npx @authensor/safeclaw. SafeClaw runs locally with sub-millisecond policy evaluation, and the free tier includes 7-day renewable keys with no credit card required. More information is available at safeclaw.onrender.com and authensor.com.