Python SDK

pip install litellm

from litellm import completion
import os
os.environ["OPENAI_API_KEY"] = "your-openai-key"
os.environ["ANTHROPIC_API_KEY"] = "your-anthropic-key"
# OpenAI
response = completion(model="openai/gpt-4o", messages=[{"role": "user", "content": "Hello!"}])
# Anthropic 
response = completion(model="anthropic/claude-sonnet-4-20250514", messages=[{"role": "user", "content": "Hello!"}])

AI Gateway (Proxy Server)

pip install 'litellm[proxy]'
litellm --model gpt-4o

import openai
client = openai.OpenAI(api_key="anything", base_url="http://0.0.0.0:4000")
response = client.chat.completions.create(
 model="gpt-4o",
 messages=[{"role": "user", "content": "Hello!"}]
)

Python SDK - A2A Protocol

from litellm.a2a_protocol import A2AClient
from a2a.types import SendMessageRequest, MessageSendParams
from uuid import uuid4
client = A2AClient(base_url="http://localhost:10001")
request = SendMessageRequest(
 id=str(uuid4()),
 params=MessageSendParams(
 message={
 "role": "user",
 "parts": [{"kind": "text", "text": "Hello!"}],
 "messageId": uuid4().hex,
 }
 )
)
response = await client.send_message(request)

AI Gateway (Proxy Server)

from a2a.client import A2ACardResolver, A2AClient
from a2a.types import MessageSendParams, SendMessageRequest
from uuid import uuid4
import httpx
base_url = "http://localhost:4000/a2a/my-agent" # LiteLLM proxy + agent name
headers = {"Authorization": "Bearer sk-1234"} # LiteLLM Virtual Key
async with httpx.AsyncClient(headers=headers) as httpx_client:
 resolver = A2ACardResolver(httpx_client=httpx_client, base_url=base_url)
 agent_card = await resolver.get_agent_card()
 client = A2AClient(httpx_client=httpx_client, agent_card=agent_card)
 request = SendMessageRequest(
 id=str(uuid4()),
 params=MessageSendParams(
 message={
 "role": "user",
 "parts": [{"kind": "text", "text": "Hello!"}],
 "messageId": uuid4().hex,
 }
 )
 )
 response = await client.send_message(request)

Python SDK - MCP Bridge

from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client
from litellm import experimental_mcp_client
import litellm
server_params = StdioServerParameters(command="python", args=["mcp_server.py"])
async with stdio_client(server_params) as (read, write):
 async with ClientSession(read, write) as session:
 await session.initialize()
 # Load MCP tools in OpenAI format
 tools = await experimental_mcp_client.load_mcp_tools(session=session, format="openai")
 # Use with any LiteLLM model
 response = await litellm.acompletion(
 model="gpt-4o",
 messages=[{"role": "user", "content": "What's 3 + 5?"}],
 tools=tools
 )

AI Gateway - MCP Gateway

curl -X POST 'http://0.0.0.0:4000/v1/chat/completions' \
 -H 'Authorization: Bearer sk-1234' \
 -H 'Content-Type: application/json' \
 -d '{
 "model": "gpt-4o",
 "messages": [{"role": "user", "content": "Summarize the latest open PR"}],
 "tools": [{
 "type": "mcp",
 "server_url": "litellm_proxy/mcp/github",
 "server_label": "github_mcp",
 "require_approval": "never"
 }]
 }'

Use with Cursor IDE

{
 "mcpServers": {
 "LiteLLM": {
 "url": "http://localhost:4000/mcp",
 "headers": {
 "x-litellm-api-key": "Bearer sk-1234"
 }
 }
 }
}