LibreChat-AI/LibreChat

Enhanced ChatGPT Clone: Features Agents, MCP, Skills, DeepSeek, Anthropic, AWS, OpenAI, Responses API, Azure, Groq, o1, GPT-5, Mistral, OpenRouter, Vertex...

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Summary Information

Updated 1 hour ago
Added to GitGenius on September 24th, 2026
Created on February 12th, 2023
Open Issues & Pull Requests: 856 (+0)
GitHub issues: Enabled
Number of forks: 9,320
Total Stargazers: 45,391 (+3)
Total Subscribers: 217 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 5.8 hours
Mean response time: 16.9 days
90th percentile: 27.5 days
Tracked items: 2,240

How this project is maintained

Roughly one issue in three opened in the past year never receives a reply. 89% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Work labelled "❓ question" is answered fastest, typically in under an hour, while "🗺️ Chat UI Shell" waits about 2 weeks. Almost all tracked open issues have seen activity in the last three months. 82% of issues opened in the past year have been closed, leaving a working backlog.

Charts & Analytics

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Issue Activity (beta)

Open issues: 410
New in 7 days: 45
Closed in 7 days: 20
Avg open age: 209 days
Stale 30+ days: 61
Stale 90+ days: 29

Recent activity

Opened in 7 days: 37
Closed in 7 days: 19
Comments in 7 days: 10
Events in 7 days: 38

Top labels

  • 🐛 bug (1,948)
  • ✨ enhancement (1,220)
  • ❓ question (107)
  • 🗺️ Chat Features (85)
  • 🗺️ Chat Frontend (79)
  • ♿ a11y (52)
  • 🗺️ Backend Platform (49)
  • 🗺️ Server Core (47)

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Detailed Description

LibreChat is a self-hosted web interface for interacting with multiple AI models that provides an alternative to proprietary chat platforms.

The tool addresses the need for a unified, privacy-preserving interface to access diverse AI providers without vendor lock-in. It works by aggregating support for numerous language models—including those from OpenAI, Anthropic, Google, AWS, Azure, and others—into a single web application. Users can switch between models, leverage agent capabilities with tool integration, and employ specialized features like code interpretation and artifact generation. The platform supports advanced workflows through Model Context Protocol integration, custom skills, and OpenAPI-based actions.

Organizations and individuals seeking self-hosted AI infrastructure should consider this tool if they want to avoid reliance on a single provider's interface, need multi-user authentication with secure access controls, or require the ability to run locally or on private infrastructure. The project suits teams that value flexibility in model selection and want to maintain control over their conversation data. It distinguishes itself through breadth of provider support, agent and skill frameworks, and workspace isolation capabilities rather than focusing on a single model or use case.

Development activity shows sustained engineering effort across multiple dimensions. The project maintains active feature development with recent additions including public agent APIs with OpenAPI specification serving, experimental workspace attachment for conversation isolation, and a trace viewer for inspecting agent execution. Work continues on reliability improvements for Model Context Protocol handling, including per-request header management and OAuth coordination across replicas. Performance optimization remains an ongoing priority, with recent work on incremental Markdown streaming and virtualized model search. The codebase is written in TypeScript and includes comprehensive documentation alongside active community engagement channels.