SDK Integration for Developers

The LeanMCP AI Gateway works with any OpenAI-compatible SDK or library. Simply change the base URL and API key to route requests through the gateway.

Key Insight: Any library that supports a custom baseURL or base_url parameter can use the LeanMCP AI Gateway.

Prerequisites

Get Credits

Purchase credits at leanmcp.com

Create API Key

Create an API key at leanmcp.com/api-keys with SDK permissions

Gateway Endpoints

Provider	Base URL
OpenAI	`https://aigateway.leanmcp.com/v1/openai`
Anthropic	`https://aigateway.leanmcp.com/v1/anthropic`
xAI (Grok)	`https://aigateway.leanmcp.com/v1/xai`
Fireworks	`https://aigateway.leanmcp.com/v1/fireworks`
ElevenLabs	`https://aigateway.leanmcp.com/v1/elevenlabs`

Official SDKs

OpenAI SDK

TypeScript/JavaScript
Python
cURL

import OpenAI from 'openai';

const client = new OpenAI({
  baseURL: 'https://aigateway.leanmcp.com/v1/openai',
  apiKey: process.env.LEANMCP_API_KEY, // leanmcp_xxx
});

const response = await client.chat.completions.create({
  model: 'gpt-5.2',
  messages: [
    { role: 'user', content: 'Hello!' }
  ],
});

console.log(response.choices[0].message.content);

from openai import OpenAI
import os

client = OpenAI(
    base_url="https://aigateway.leanmcp.com/v1/openai",
    api_key=os.environ.get("LEANMCP_API_KEY"),  # leanmcp_xxx
)

response = client.chat.completions.create(
    model="gpt-5.2",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

curl https://aigateway.leanmcp.com/v1/openai/chat/completions \
  -H "Authorization: Bearer leanmcp_your_api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5.2",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Anthropic SDK

TypeScript/JavaScript
Python

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  baseURL: 'https://aigateway.leanmcp.com/v1/anthropic',
  apiKey: process.env.LEANMCP_API_KEY,
});

const response = await client.messages.create({
  model: 'claude-sonnet-4-5-20250929',
  max_tokens: 1024,
  messages: [
    { role: 'user', content: 'Hello!' }
  ],
});

console.log(response.content[0].text);

import anthropic
import os

client = anthropic.Anthropic(
    base_url="https://aigateway.leanmcp.com/v1/anthropic",
    api_key=os.environ.get("LEANMCP_API_KEY"),
)

response = client.messages.create(
    model="claude-sonnet-4-5-20250929",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.content[0].text)

Streaming

OpenAI Streaming
Anthropic Streaming

import OpenAI from 'openai';

const client = new OpenAI({
  baseURL: 'https://aigateway.leanmcp.com/v1/openai',
  apiKey: process.env.LEANMCP_API_KEY,
});

const stream = await client.chat.completions.create({
  model: 'gpt-5.2',
  messages: [{ role: 'user', content: 'Write a poem' }],
  stream: true,
});

for await (const chunk of stream) {
  process.stdout.write(chunk.choices[0]?.delta?.content || '');
}

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  baseURL: 'https://aigateway.leanmcp.com/v1/anthropic',
  apiKey: process.env.LEANMCP_API_KEY,
});

const stream = client.messages.stream({
  model: 'claude-sonnet-4-5-20250929',
  max_tokens: 1024,
  messages: [{ role: 'user', content: 'Write a poem' }],
});

for await (const event of stream) {
  if (event.type === 'content_block_delta') {
    process.stdout.write(event.delta.text);
  }
}

Framework Integrations

LangChain

TypeScript
Python

import { ChatOpenAI } from '@langchain/openai';

const model = new ChatOpenAI({
  modelName: 'gpt-5.2',
  configuration: {
    baseURL: 'https://aigateway.leanmcp.com/v1/openai',
    apiKey: process.env.LEANMCP_API_KEY,
  },
});

const response = await model.invoke('Hello!');
console.log(response.content);

from langchain_openai import ChatOpenAI
import os

model = ChatOpenAI(
    model="gpt-5.2",
    base_url="https://aigateway.leanmcp.com/v1/openai",
    api_key=os.environ.get("LEANMCP_API_KEY"),
)

response = model.invoke("Hello!")
print(response.content)

Vercel AI SDK

import { openai } from '@ai-sdk/openai';
import { generateText } from 'ai';

const customOpenAI = openai.configure({
  baseURL: 'https://aigateway.leanmcp.com/v1/openai',
  apiKey: process.env.LEANMCP_API_KEY,
});

const { text } = await generateText({
  model: customOpenAI('gpt-5.2'),
  prompt: 'Hello!',
});

console.log(text);

LlamaIndex

from llama_index.llms.openai import OpenAI
import os

llm = OpenAI(
    model="gpt-5.2",
    api_base="https://aigateway.leanmcp.com/v1/openai",
    api_key=os.environ.get("LEANMCP_API_KEY"),
)

response = llm.complete("Hello!")
print(response.text)

Adding Request Context

For better tracking and analytics, add custom headers to your requests:

const response = await client.chat.completions.create({
  model: 'gpt-5.2',
  messages: messages,
}, {
  headers: {
    'X-User-ID': userId,           // Track per-user usage
    'X-Session-ID': sessionId,     // Group requests by session
    'X-Request-Source': 'web-app', // Identify request source
    'X-Feature': 'chat',           // Tag by feature
  }
});

These headers appear in your dashboard and enable:

Per-user usage tracking and limits
Session-based request grouping
Feature-level analytics
Source attribution

OpenAI-Compatible Libraries

Any library that supports a custom base URL works with the LeanMCP AI Gateway:

Library	Configuration
openai (official)	`baseURL` parameter
anthropic (official)	`baseURL` parameter
langchain	`base_url` in configuration
llama-index	`api_base` parameter
vercel/ai	`baseURL` in configure
litellm	`api_base` parameter
guidance	Custom OpenAI client
instructor	Pass custom OpenAI client

Generic Pattern

// Any OpenAI-compatible library
const client = new SomeAILibrary({
  baseURL: 'https://aigateway.leanmcp.com/v1/openai', // or /anthropic, /xai, etc.
  apiKey: 'leanmcp_your_api_key',
});

Environment Setup

Recommended: Environment Variables

# .env file
LEANMCP_API_KEY=leanmcp_your_api_key_here
LEANMCP_OPENAI_BASE_URL=https://aigateway.leanmcp.com/v1/openai
LEANMCP_ANTHROPIC_BASE_URL=https://aigateway.leanmcp.com/v1/anthropic

Multiple Environments

const getBaseURL = () => {
  if (process.env.NODE_ENV === 'development') {
    return 'https://aigateway.leanmcp.com/v1/openai'; // Use gateway in dev
  }
  return 'https://api.openai.com/v1'; // Direct in production (optional)
};

const client = new OpenAI({
  baseURL: getBaseURL(),
  apiKey: process.env.OPENAI_API_KEY,
});

Error Handling

try {
  const response = await client.chat.completions.create({
    model: 'gpt-5.2',
    messages: [{ role: 'user', content: 'Hello' }],
  });
} catch (error) {
  if (error.status === 401) {
    console.error('Invalid API key');
  } else if (error.status === 402) {
    console.error('Insufficient credits');
  } else if (error.status === 429) {
    console.error('Rate limited');
  } else {
    console.error('API error:', error.message);
  }
}

Benefits for Developers

Unified Logging

All AI requests logged in one dashboard

User Tracking

Track usage per user with custom headers

Cost Attribution

Know which features drive AI costs

A/B Testing

Test different models and prompts

Security

Block malicious users and sensitive data

Rate Limiting

Set limits per user or globally

Next Steps

Security Features

Block users and protect sensitive data

Token Optimization

A/B testing and cost reduction

Observability

Monitor all requests

For Developers

Advanced developer features

Overview

For Users

For Developers

Features

SDK Integration

SDK Integration for Developers

Prerequisites

Gateway Endpoints

Official SDKs

OpenAI SDK

Anthropic SDK

Streaming

Framework Integrations

LangChain

Vercel AI SDK

LlamaIndex

Adding Request Context

OpenAI-Compatible Libraries

Generic Pattern

Environment Setup

Recommended: Environment Variables

Multiple Environments

Error Handling

Benefits for Developers

Unified Logging

User Tracking

Cost Attribution

A/B Testing

Security

Rate Limiting

Next Steps

Security Features

Token Optimization

Observability

For Developers

​SDK Integration for Developers

​Prerequisites

​Gateway Endpoints

​Official SDKs

​OpenAI SDK

​Anthropic SDK

​Streaming

​Framework Integrations

​LangChain

​Vercel AI SDK

​LlamaIndex

​Adding Request Context

​OpenAI-Compatible Libraries

​Generic Pattern

​Environment Setup

​Recommended: Environment Variables

​Multiple Environments

​Error Handling

​Benefits for Developers

Unified Logging

User Tracking

Cost Attribution

A/B Testing

Security

Rate Limiting

​Next Steps

Security Features

Token Optimization

Observability

For Developers

SDK Integration for Developers

Prerequisites

Gateway Endpoints

Official SDKs

OpenAI SDK

Anthropic SDK

Streaming

Framework Integrations

LangChain

Vercel AI SDK

LlamaIndex

Adding Request Context

OpenAI-Compatible Libraries

Generic Pattern

Environment Setup

Recommended: Environment Variables

Multiple Environments

Error Handling

Benefits for Developers

Next Steps