litellm: Unifying 100+ LLM APIs via OpenAI Format MCP Server
litellm: Unifying 100+ LLM APIs via OpenAI Format MCP Server
litellm, a Python SDK and MCP Server, acts as an LLM Gateway, providing a unified interface to over 100 different Large Language Model (LLM) APIs. It standardizes these diverse models, including Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, Replicate, and Groq, all accessible through the familiar OpenAI API format. With over 53,000 GitHub stars, litellm simplifies the integration of various AI models into your applications.
Consistent LLM Access with OpenAI Format
The core utility of litellm lies in its ability to abstract away the unique API quirks of numerous LLMs. By presenting all supported models through an OpenAI-compatible format, developers can write code once and switch between providers or even combine them without significant refactoring. This consistency is crucial for projects requiring flexibility in their AI backend or for those experimenting with different models to find the best fit.
Deploying the Proxy Server
litellm functions as an MCP Server, deployable as a proxy or LLM gateway. This server component allows applications to route requests through a single endpoint, which then handles the translation and forwarding to the chosen LLM provider. This architecture is particularly useful for managing API keys, implementing rate limiting, or adding logging across multiple LLM integrations. The project provides quick deployment options for platforms like Render and Railway, streamlining the setup process.
Supported LLM Providers
The breadth of LLM providers supported by litellm is extensive, covering many of the major players in the AI landscape. This includes:
- Bedrock
- Azure
- OpenAI
- VertexAI
- Cohere
- Anthropic
- Sagemaker
- HuggingFace
- Replicate
- Groq
- TogetherAI
This wide array of integrations means developers are not locked into a single provider and can leverage the strengths of different models for various tasks.