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Provider-native integration patterns for OpenAI, Anthropic, and Google clients with Mnexium routing, header conventions, and parity-safe request shapes.

SDK Integration

Choose Your Integration Style

Mnexium supports two integration approaches. Choose based on your needs:

OpenAI Connector (Recommended)

Use the OpenAI SDK for all providers (OpenAI, Claude, Gemini). Same code, same response format, just change the model name.

  • Unified API across all providers
  • Full mnx support in request body
  • Consistent response format
  • Lowest integration complexity

Native SDKs

Use each provider's official SDK with their native endpoints and response formats.

  • Native SDK features and types
  • Provider-specific response formats
  • mnx via headers (SDKs strip body params)
  • Different base URLs per provider

Code Examples

Use the OpenAI SDK to call any provider through Mnexium's unified endpoint. Just change the model name and pass the appropriate provider key.

ProviderHeaderExample Models
OpenAIx-openai-keygpt-4o, gpt-4o-mini
Anthropicx-anthropic-keyclaude-sonnet-4-20250514
Googlex-google-keygemini-2.0-flash-lite
js
import OpenAI from "openai";

const BASE_URL = "https://mnexium.com/api/v1";

// OpenAI client
const openai = new OpenAI({
  baseURL: BASE_URL,
  defaultHeaders: {
    "x-mnexium-key": process.env.MNX_KEY,
    "x-openai-key": process.env.OPENAI_API_KEY,
  },
});

// Claude client (via OpenAI SDK)
const claude = new OpenAI({
  baseURL: BASE_URL,
  defaultHeaders: {
    "x-mnexium-key": process.env.MNX_KEY,
    "x-anthropic-key": process.env.CLAUDE_API_KEY,
  },
});

// Gemini client (via OpenAI SDK)
const gemini = new OpenAI({
  baseURL: BASE_URL,
  defaultHeaders: {
    "x-mnexium-key": process.env.MNX_KEY,
    "x-google-key": process.env.GEMINI_KEY,
  },
});

// All calls use the same API!
const openaiResponse = await openai.chat.completions.create({
  model: "gpt-4o",
  messages: [{ role: "user", content: "What do you know about me?" }],
  mnx: { subject_id: "user_123", recall: true },
});

const claudeResponse = await claude.chat.completions.create({
  model: "claude-sonnet-4-20250514",
  messages: [{ role: "user", content: "What do you know about me?" }],
  mnx: { subject_id: "user_123", recall: true },
});

const geminiResponse = await gemini.chat.completions.create({
  model: "gemini-2.0-flash-lite",
  messages: [{ role: "user", content: "What do you know about me?" }],
  mnx: { subject_id: "user_123", recall: true },
});

Cross-Provider Memory Sharing

Memories learned with one provider are automatically available to all others. Use the same subject_id across providers to share context.

js
// Learn a fact with OpenAI
await openai.chat.completions.create({
  model: "gpt-4o-mini",
  messages: [{ role: "user", content: "My favorite color is purple" }],
  mnx: { subject_id: "user_123", learn: "force" },
});

// Recall with Claude - it knows the color!
const claudeResponse = await claude.chat.completions.create({
  model: "claude-sonnet-4-20250514",
  messages: [{ role: "user", content: "What is my favorite color?" }],
  mnx: { subject_id: "user_123", recall: true },
});
// Claude responds: "Your favorite color is purple!"

This enables multi-model workflows where each task can use the most appropriate model while keeping user context consistent.