LibreChat: The Self-Hosted ChatGPT Alternative with AI Agents and MCP Support

TL;DR for AI Agents

LibreChat is a self-hosted, open-source AI chat platform (33K+ GitHub stars) that aggregates all major AI providers into one unified interface. Key capabilities: multi-provider support (OpenAI, Anthropic, Google, AWS Bedrock, Azure, local models via Ollama), built-in AI Agents with no-code builder, Model Context Protocol (MCP) integration for tool connectivity, Code Interpreter with sandboxed execution in 8+ languages, web search, RAG file chat, image generation, and enterprise-ready auth (OAuth2, LDAP). Docker deployment with docker-compose. Active development with weekly releases.

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If you’re paying for ChatGPT Plus, Claude Pro, and Gemini Advanced separately—and still can’t use them in one place—LibreChat might be exactly what you need. It’s an open-source, self-hosted alternative that puts you in control of your AI conversations while unifying all the major providers under one roof.

What is LibreChat?

LibreChat is an enhanced ChatGPT clone that’s grown into something far more powerful than its inspiration. With 33,700+ GitHub stars and an incredibly active development cycle (multiple releases per week), it’s become the go-to solution for developers and organizations who want:

• Privacy: Your conversations stay on your infrastructure
• Flexibility: Switch between OpenAI, Anthropic, Google, and dozens of other providers mid-conversation
• Cost Control: Use your own API keys instead of expensive subscriptions
• Customization: AI Agents, custom presets, and Model Context Protocol (MCP) support

Think of it as a ChatGPT-like interface that speaks to every AI provider, not just OpenAI.

Key Features

Multi-Provider AI Model Selection

LibreChat isn’t locked into one AI vendor. Out of the box, it supports:

Cloud Providers:

• OpenAI (GPT-4o, GPT-5, o1, o3)
• Anthropic (Claude 3.5 Sonnet, Claude 3 Opus)
• Google (Gemini Pro, Gemini Ultra)
• AWS Bedrock
• Azure OpenAI
• Vertex AI

Local & Alternative Providers:

• Ollama (run Llama 3, Mistral, Qwen locally)
• Groq (ultra-fast inference)
• DeepSeek
• Together.ai
• OpenRouter
• Mistral AI
• Perplexity
• Cohere

Why this matters: You can start a conversation with GPT-4o, switch to Claude for code review, then use a local Llama model for sensitive data—all in the same chat session.

AI Agents (No-Code Custom Assistants)

LibreChat’s Agent feature represents a paradigm shift. You can build specialized AI assistants without writing code:

Agent: "Code Reviewer"
├── Model: Claude 3.5 Sonnet
├── System Prompt: "You are a senior software engineer..."
├── Tools:
│   ├── Code Interpreter
│   ├── File Search
│   └── DALL-E (for architecture diagrams)
└── Files: coding-standards.md, security-checklist.md

Agent capabilities:

• Attach tools like DALL-E, web search, calculators
• File management and RAG (retrieval-augmented generation)
• Code execution in sandboxed environments
• Share agents with specific users or groups
• Agent Marketplace for community-built assistants

Model Context Protocol (MCP) Integration

LibreChat is an official MCP client, meaning it can connect to any MCP server for tool integration. This is huge for automation:

# librechat.yaml MCP configuration
mcp:
  servers:
    - name: "filesystem"
      command: "npx"
      args: ["-y", "@modelcontextprotocol/server-filesystem", "/data"]
    - name: "github"
      command: "npx"
      args: ["-y", "@modelcontextprotocol/server-github"]
      env:
        GITHUB_TOKEN: "${GITHUB_TOKEN}"

Your AI can now read/write files, interact with GitHub, query databases, or connect to any service with an MCP server.

Code Interpreter API

Unlike ChatGPT’s Code Interpreter, LibreChat’s is completely sandboxed and supports 8 programming languages:

• Python
• Node.js (JavaScript/TypeScript)
• Go
• C/C++
• Java
• PHP
• Rust
• Fortran

Features:

• Secure, isolated execution
• Upload files, process them, download outputs
• No data leaves your infrastructure
• Works with any connected AI model

Web Search

Built-in web search that combines:

• Search providers (Brave, Google, etc.)
• Content scrapers
• Result rerankers (Jina)

Your AI can search the internet, retrieve relevant content, and incorporate it into responses—all without leaving the chat.

Artifacts (Generative UI)

Create interactive content directly in chat:

• React components: Build and preview UI
• HTML pages: Generate web content
• Mermaid diagrams: Visualize architectures, flowcharts, sequences

The AI generates the code, and LibreChat renders it live. Iterate on designs without leaving the conversation.

Image Generation & Editing

Multiple providers for visual content:

• GPT-Image-1: Text-to-image and image editing
• DALL-E 3/2: OpenAI’s image generation
• Stable Diffusion: Run locally
• Flux: Latest open-source image model
• MCP servers: Any image generation tool via MCP

Enterprise Features

LibreChat is built for real deployments:

Authentication:

• OAuth2 (Google, GitHub, Microsoft, etc.)
• LDAP/Active Directory
• Email verification
• API keys for programmatic access

Multi-User:

• User management with roles
• Token spend tracking
• Usage limits per user
• Moderation tools

Scaling:

• Resumable streams (never lose a response)
• Multi-tab/multi-device sync
• Redis support for horizontal scaling
• Works from single-server to enterprise clusters

Installation

LibreChat provides multiple deployment options. Docker Compose is the simplest:

Quick Start with Docker

# Clone the repository
git clone https://github.com/danny-avila/LibreChat.git
cd LibreChat

# Copy environment template
cp .env.example .env

# Configure your API keys in .env
# OPENAI_API_KEY=sk-...
# ANTHROPIC_API_KEY=sk-ant-...

# Start LibreChat
docker compose up -d

Access LibreChat at http://localhost:3080.

One-Click Deployments

LibreChat offers templates for:

• Railway
• Zeabur
• Sealos

Configuration

The main configuration lives in librechat.yaml:

version: 1.2.1

# Enable/disable features
features:
  agents: true
  codeArtifacts: true
  webSearch: true

# AI Endpoints
endpoints:
  openAI:
    apiKey: "${OPENAI_API_KEY}"
    models:
      default: ["gpt-4o", "gpt-4o-mini", "o1-preview"]
  
  anthropic:
    apiKey: "${ANTHROPIC_API_KEY}"
    models:
      default: ["claude-3-5-sonnet-20241022", "claude-3-opus-20240229"]
  
  # Custom endpoint for local Ollama
  custom:
    - name: "Ollama"
      apiKey: "ollama"
      baseURL: "http://localhost:11434/v1"
      models:
        default: ["llama3.2", "mistral", "codellama"]

# MCP Servers
mcp:
  servers:
    - name: filesystem
      command: npx
      args: ["-y", "@modelcontextprotocol/server-filesystem", "/app/data"]

Advanced Use Cases

Private AI for Teams

Deploy LibreChat on your infrastructure with:

• LDAP authentication tied to your corporate directory
• Token budgets per department
• Audit logs for compliance
• No data sent to third parties (use local models)

AI Development Platform

Use LibreChat as your AI experimentation lab:

• Test prompts across multiple models simultaneously
• Build and share custom agents
• Iterate on system prompts with conversation branching
• Export conversations for fine-tuning datasets

Customer Support Backend

Combine LibreChat’s features:

• Agents trained on your documentation (RAG)
• MCP connection to your ticketing system
• Code Interpreter for technical support
• Web search for latest product updates

Comparison: LibreChat vs Alternatives

Feature	LibreChat	ChatGPT	Open WebUI	Anything LLM
Multi-provider	✅ All major	❌ OpenAI only	✅ Ollama focus	✅ Yes
MCP Support	✅ Official	❌	❌	❌
AI Agents	✅ No-code	✅ GPTs	❌	✅ Yes
Code Interpreter	✅ 8 languages	✅ Python	❌	❌
Self-hosted	✅	❌	✅	✅
Enterprise Auth	✅ OAuth/LDAP	❌	⚠️ Basic	⚠️ Basic
GitHub Stars	33.7K	N/A	73K	54K

LibreChat sits in the sweet spot: more features than Open WebUI, more provider flexibility than ChatGPT, and stronger enterprise support than AnythingLLM.

When to Use LibreChat

Ideal for:

• Teams needing multi-provider AI access
• Organizations with data privacy requirements
• Developers building AI-powered workflows
• Companies wanting ChatGPT-like UX without vendor lock-in

Consider alternatives if:

• You only use OpenAI → ChatGPT might be simpler
• You only need local models → Open WebUI is lighter
• You need voice-first interface → Look at voice-specific tools

Community & Support

LibreChat has an active community:

• Discord: Real-time help and discussions
• GitHub Issues: Bug reports and feature requests
• YouTube: Official tutorials and walkthroughs
• Documentation: Comprehensive at docs.librechat.ai

The project releases updates frequently—sometimes multiple times per week. Breaking changes are documented in the changelog.

Final Thoughts

LibreChat is what happens when open-source meets enterprise needs. It’s not just a ChatGPT clone—it’s a full AI platform that gives you control over providers, privacy, and customization.

The MCP integration alone makes it worth exploring. As the AI tool ecosystem expands, having a single interface that can connect to any MCP server means your chat interface grows with the ecosystem.

If you’re managing AI access for a team, tired of juggling multiple AI subscriptions, or need an AI platform you can actually self-host—LibreChat delivers.

Links:

• GitHub: github.com/danny-avila/LibreChat
• Website: librechat.ai
• Docs: docs.librechat.ai
• Discord: discord.librechat.ai