LocalAI
LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.
What is LocalAI?
LocalAI is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to localai is the open-source ai engine. run any model - llms, vision, voice, image, video - on any hardware. no gpu required.
LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.
This server falls under the Cloud Services category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- LocalAI is the open-source AI engine. Run any model - LLMs,
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx localaiConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use LocalAI
LocalAI is an open-source, self-hosted AI engine that provides an OpenAI-compatible REST API for running LLMs, vision models, image generation, voice synthesis, and video models entirely on your own hardware — no GPU required. It pulls model backends on demand as OCI container images and supports formats including GGUF (llama.cpp), Stable Diffusion, Whisper, and more. Developers use LocalAI to replace cloud AI APIs with a local drop-in alternative that preserves privacy, eliminates per-token costs, and supports MCP-based agentic workflows with built-in tool use and RAG capabilities.
Prerequisites
- Docker installed (recommended) or Go 1.21+ for building from source
- At least 8 GB RAM for small models; 16 GB+ recommended for 7B parameter models
- NVIDIA GPU with CUDA drivers (optional) for accelerated inference — CPU-only mode is supported
- An MCP client such as Claude Desktop or Cursor
- Sufficient disk space for model files (GGUF models range from 2 GB to 40 GB+)
Start LocalAI with Docker (CPU mode)
Pull and run the LocalAI Docker image. This starts the OpenAI-compatible API server on port 8080. For NVIDIA GPU acceleration, use the cuda image tag instead.
docker run -ti --name local-ai -p 8080:8080 localai/localai:latestLoad a model
Use the local-ai CLI to download and run a model. LocalAI supports Hugging Face GGUF models, Ollama model names, and its own model gallery.
local-ai run llama-3.2-1b-instruct:q4_k_m
# Or load from Hugging Face:
local-ai run huggingface://TheBloke/phi-2-GGUF/phi-2.Q8_0.gguf
# Or from Ollama registry:
local-ai run ollama://gemma:2bVerify the API is responding
Test that LocalAI's OpenAI-compatible endpoint is working by sending a simple chat completion request.
curl http://localhost:8080/v1/chat/completions \
-H 'Content-Type: application/json' \
-d '{"model": "llama-3.2-1b-instruct", "messages": [{"role": "user", "content": "Hello!"}]}'Configure the MCP server in your AI client
Add LocalAI as an MCP server in your Claude Desktop configuration. Since LocalAI exposes an OpenAI-compatible API, configure the base URL to point to your local instance.
Enable GPU acceleration (optional)
For faster inference with an NVIDIA GPU, use the CUDA-enabled Docker image and pass the --gpus flag.
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-13LocalAI Examples
Client configuration
Add LocalAI to claude_desktop_config.json. The command runs npx localai which connects to your locally running LocalAI instance.
{
"mcpServers": {
"localai": {
"command": "npx",
"args": ["localai"],
"env": {
"LOCALAI_BASE_URL": "http://localhost:8080",
"LOCALAI_MODEL": "llama-3.2-1b-instruct"
}
}
}
}Prompts to try
Once LocalAI is running and connected, use these prompts to interact with your local AI models.
- "Use the local model to summarize this document without sending it to any external API"
- "Generate an image of a sunset over mountains using the local Stable Diffusion model"
- "Transcribe this audio file using the local Whisper model"
- "Run a local LLM to classify these customer support tickets by category and urgency"Troubleshooting LocalAI
Model loading fails with out-of-memory errors
Use a quantized model with a smaller variant (e.g. q4_k_m instead of q8_0 or fp16). Check available RAM with 'free -h' (Linux) or Activity Monitor (macOS) and choose a model that fits within your system's available memory.
API returns 'model not found' errors
Confirm the model name in your API request exactly matches the name LocalAI assigned during loading. List loaded models with 'curl http://localhost:8080/v1/models' and use the returned id value in your requests.
Docker container exits immediately on Apple Silicon Mac
LocalAI's standard Docker images target x86_64. On Apple Silicon, use the 'latest-aio-cpu' image or install the macOS desktop app from localai.io which includes native ARM64 binaries.
Frequently Asked Questions about LocalAI
What is LocalAI?
LocalAI is a Model Context Protocol (MCP) server that localai is the open-source ai engine. run any model - llms, vision, voice, image, video - on any hardware. no gpu required. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install LocalAI?
Follow the installation instructions on the LocalAI GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with LocalAI?
LocalAI works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is LocalAI free to use?
Yes, LocalAI is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
LocalAI Alternatives — Similar Cloud Services Servers
Looking for alternatives to LocalAI? Here are other popular cloud services servers you can use with Claude, Cursor, and VS Code.
Open WebUI
★ 138.2kUser-friendly AI Interface (Supports Ollama, OpenAI API, ...)
Anything LLM
★ 60.4kThe all-in-one AI productivity accelerator. On device and privacy first with no annoying setup or configuration.
Nacos
★ 33.0kan easy-to-use dynamic service discovery, configuration and service management platform for building AI cloud native applications.
Xiaozhi ESP32
★ 26.7k本项目为xiaozhi-esp32提供后端服务，帮助您快速搭建ESP32设备控制服务器。Backend service for xiaozhi-esp32, helps you quickly build an ESP32 device control server.
Gateway
★ 11.8kA blazing fast AI Gateway with integrated guardrails. Route to 1,600+ LLMs, 50+ AI Guardrails with 1 fast & friendly API.
Nginx UI
★ 11.2kYet another WebUI for Nginx
Browse More Cloud Services MCP Servers
Explore all cloud services servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.
Set Up LocalAI in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
Ready to use LocalAI?
Browse our complete directory of 33,000+ MCP servers, read setup guides for your editor, and start building with the Model Context Protocol.