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Enhanced ChatGPT Clone: Features Agents, MCP, DeepSeek, Anthropic, AWS, OpenAI, Responses API, Azure, Groq, o1, GPT-5, Mistral, OpenRouter, Vertex AI, Gemini, Artifacts, AI model switching, message search, Code Interpreter, langchain, DALL-E-3, OpenAPI Actions, Functions, Secure Multi-User Auth, Presets, open-source for self-hosting. Active.
https://librechat.ai/
aianthropicartifactsawsazurechatgptchatgpt-cloneclaudeclonedeepseekgeminigooglegpt-5librechatmcpo1openairesponses-apivisionwebui
f5c4deac28
* 📦 chore: Bump @modelcontextprotocol/sdk to v1.29.0 * ♻️ refactor: Extract WWW-Authenticate Probe Helper for MCP OAuth * 🔐 fix: Prefer WWW-Authenticate resource_metadata Hint for MCP OAuth Per RFC 9728 §5.1, the `resource_metadata=<url>` parameter in a 401 `WWW-Authenticate: Bearer` challenge is the authoritative protected-resource metadata source. Path-aware `.well-known` discovery was winning over the hint, so split deployments that serve valid-but-wrong metadata at the path-aware endpoint stranded OAuth at defunct authorization servers. Threads the hint through `discoverOAuthProtectedResourceMetadata` via `opts.resourceMetadataUrl` in both startup detection and the OAuth handler, matching the behavior of Claude Desktop, the MCP Inspector, OpenAI tooling, and Microsoft Copilot Studio. Fixes #12761. * 🧵 fix: Thread OAuth-Aware fetchFn Through Resource-Metadata Probe Without this, admin-configured `oauthHeaders` (e.g. a gateway API key that fronts the MCP endpoint) were stripped from the probe, causing the gateway to 401 for the wrong reason and masking the real `WWW-Authenticate` hint. The helper now accepts a FetchLike and defaults to global fetch, so the startup detection path is unchanged while the handler passes its OAuth- aware wrapper through. * 🧹 refactor: Address MCP OAuth Probe Review Findings - Thread `fetchFn` through `probeResourceMetadataHint` so admin-configured `oauthHeaders` reach the probe (a gateway API key that fronts the MCP endpoint would otherwise 401 us for the wrong reason and hide the real Bearer challenge). - Skip the redundant HEAD request in `checkAuthErrorFallback` when the probe already observed a 401/403; fall back to a fresh HEAD only when every probe attempt threw (transient network error). - Narrow the oauth barrel: drop `export * from './resourceHint'` so the helper stays an internal module. - Add `scope` extraction coverage (`Bearer scope="read write"`) and a 403-only observation path; isolate `MCP_OAUTH_ON_AUTH_ERROR=true` in a dedicated suite so precise-outcome tests aren't muddied by the safety net. * ✅ fix: Use Zod Schema in MCP Reconnection-Storm Test Tool MCP SDK 1.28 tightened `McpServer.tool()` to require Zod schemas instead of plain JSON-Schema objects. Swap the `{ message: { type: 'string' } }` shape for `z.string()` so the fixture server spins up under SDK 1.29. * 🛡️ fix: Harden MCP OAuth resource_metadata Hint Against SSRF The `resource_metadata` URL is echoed from an untrusted MCP server, so handing it straight to the SDK lets a malicious server redirect discovery at private IPs, the cloud metadata service, or any host the admin did not intend to reach. Caught by the Copilot review on #12763. - `handler.ts`: run the hint through the same `validateOAuthUrl` / `allowedDomains` gate that already guards the authorization-server URL; drop it and fall back to path-aware discovery on rejection. - `detectOAuth.ts`: no admin-scoped allowedDomains here, so apply a strict `isSSRFTarget` + DNS resolution check and silently discard any hint pointing at a private/loopback/metadata address. - Tests cover both the hostname-list and DNS-resolution rejection paths and assert the SDK falls back to path-aware discovery unharmed. * 🧪 test: Mock ~/auth in fallback Suite for Consistency Matches the main `detectOAuth.test.ts` mock so the SSRF guards added in the previous commit don't touch the real `~/auth` module at test time. * 🔍 fix: Scope OAuth Fallback to HEAD + Parse Multi-Scheme WWW-Authenticate Two codex findings on #12763: - **P1**: the merged `authChallenge` flag was letting POST-only 401/403 flip the `MCP_OAUTH_ON_AUTH_ERROR` fallback, misclassifying WAF/CSRF-hardened endpoints (HEAD 200 + POST 403) as OAuth-required. Rename to `headAuthChallenge` and derive it only from the HEAD probe, matching the legacy fallback's HEAD-only semantics. Add a regression test. - **P2**: the SDK's `extractWWWAuthenticateParams` only inspects the first scheme token, so multi-scheme headers like `Basic realm="api", Bearer resource_metadata="..."` silently dropped the authoritative Bearer hint. Fall back to a regex across the full header when the SDK returns nothing but Bearer is present. Add a regression test covering the multi-scheme case. * 🧽 refactor: Tighten MCP OAuth Probe Semantics Addresses the second external review pass plus codex P2: - Merge the two stacked JSDoc blocks on `probeResourceMetadataHint` into one with a proper `@returns` section. - Only short-circuit HEAD when it delivered the `resource_metadata` hint itself — a Bearer-without-params HEAD now lets POST run, since some servers surface their hint only on POST and we were missing it. - Drop the unused `scope` field from `ResourceHintProbeResult`; no caller read it, and YAGNI beats a reserved field. - Remove the redundant `OAUTH_ON_AUTH_ERROR` guard inside `checkAuthErrorFallback` — the only call site already gates on it. - Codex P2: signal "HEAD status unknown" via `null` when the HEAD probe threw and POST returned non-auth. Previously that combination leaked a `{headAuthChallenge: false}` result and silently skipped the fallback's retry HEAD, which could misclassify OAuth-required servers after a transient HEAD failure. Regression tests cover every path: Bearer-no-hint-on-HEAD + hint-on-POST, multi-scheme `Basic + Bearer` headers, HEAD-threw + POST-200 retry, and the WAF/CSRF-only POST 403 case. * 🪥 polish: Tighten Probe Null-Guard Ordering + Add Malformed-Hint Test Two NITs from the follow-up review: - Move `bearerChallenge` computation after the `!wwwAuth` guard so the variable is only derived when it can be meaningfully `true`. The early-return path is now a clean unconditional exit. - Add a regression test that asserts `Bearer resource_metadata="not-a-url"` yields `resourceMetadataUrl: undefined` without throwing, locking in the try/catch safety net in `extractHintFromHeader` and the SDK parser alike. |
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LibreChat
English · 中文
✨ Features
-
🖥️ UI & Experience inspired by ChatGPT with enhanced design and features
-
🤖 AI Model Selection:
- Anthropic (Claude), AWS Bedrock, OpenAI, Azure OpenAI, Google, Vertex AI, OpenAI Responses API (incl. Azure)
- Custom Endpoints: Use any OpenAI-compatible API with LibreChat, no proxy required
- Compatible with Local & Remote AI Providers:
- Ollama, groq, Cohere, Mistral AI, Apple MLX, koboldcpp, together.ai,
- OpenRouter, Helicone, Perplexity, ShuttleAI, Deepseek, Qwen, and more
-
- Secure, Sandboxed Execution in Python, Node.js (JS/TS), Go, C/C++, Java, PHP, Rust, and Fortran
- Seamless File Handling: Upload, process, and download files directly
- No Privacy Concerns: Fully isolated and secure execution
-
🔦 Agents & Tools Integration:
- LibreChat Agents:
- No-Code Custom Assistants: Build specialized, AI-driven helpers
- Agent Marketplace: Discover and deploy community-built agents
- Collaborative Sharing: Share agents with specific users and groups
- Flexible & Extensible: Use MCP Servers, tools, file search, code execution, and more
- Compatible with Custom Endpoints, OpenAI, Azure, Anthropic, AWS Bedrock, Google, Vertex AI, Responses API, and more
- Model Context Protocol (MCP) Support for Tools
- LibreChat Agents:
-
🔍 Web Search:
- Search the internet and retrieve relevant information to enhance your AI context
- Combines search providers, content scrapers, and result rerankers for optimal results
- Customizable Jina Reranking: Configure custom Jina API URLs for reranking services
- Learn More →
-
🪄 Generative UI with Code Artifacts:
- Code Artifacts allow creation of React, HTML, and Mermaid diagrams directly in chat
-
🎨 Image Generation & Editing
- Text-to-image and image-to-image with GPT-Image-1
- Text-to-image with DALL-E (3/2), Stable Diffusion, Flux, or any MCP server
- Produce stunning visuals from prompts or refine existing images with a single instruction
-
💾 Presets & Context Management:
- Create, Save, & Share Custom Presets
- Switch between AI Endpoints and Presets mid-chat
- Edit, Resubmit, and Continue Messages with Conversation branching
- Create and share prompts with specific users and groups
- Fork Messages & Conversations for Advanced Context control
-
💬 Multimodal & File Interactions:
- Upload and analyze images with Claude 3, GPT-4.5, GPT-4o, o1, Llama-Vision, and Gemini 📸
- Chat with Files using Custom Endpoints, OpenAI, Azure, Anthropic, AWS Bedrock, & Google 🗃️
-
🌎 Multilingual UI:
- English, 中文 (简体), 中文 (繁體), العربية, Deutsch, Español, Français, Italiano
- Polski, Português (PT), Português (BR), Русский, 日本語, Svenska, 한국어, Tiếng Việt
- Türkçe, Nederlands, עברית, Català, Čeština, Dansk, Eesti, فارسی
- Suomi, Magyar, Հայերեն, Bahasa Indonesia, ქართული, Latviešu, ไทย, ئۇيغۇرچە
-
🧠 Reasoning UI:
- Dynamic Reasoning UI for Chain-of-Thought/Reasoning AI models like DeepSeek-R1
-
🎨 Customizable Interface:
- Customizable Dropdown & Interface that adapts to both power users and newcomers
-
- Never lose a response: AI responses automatically reconnect and resume if your connection drops
- Multi-Tab & Multi-Device Sync: Open the same chat in multiple tabs or pick up on another device
- Production-Ready: Works from single-server setups to horizontally scaled deployments with Redis
-
🗣️ Speech & Audio:
- Chat hands-free with Speech-to-Text and Text-to-Speech
- Automatically send and play Audio
- Supports OpenAI, Azure OpenAI, and Elevenlabs
-
📥 Import & Export Conversations:
- Import Conversations from LibreChat, ChatGPT, Chatbot UI
- Export conversations as screenshots, markdown, text, json
-
🔍 Search & Discovery:
- Search all messages/conversations
-
👥 Multi-User & Secure Access:
- Multi-User, Secure Authentication with OAuth2, LDAP, & Email Login Support
- Built-in Moderation, and Token spend tools
-
⚙️ Configuration & Deployment:
- Configure Proxy, Reverse Proxy, Docker, & many Deployment options
- Use completely local or deploy on the cloud
-
📖 Open-Source & Community:
- Completely Open-Source & Built in Public
- Community-driven development, support, and feedback
For a thorough review of our features, see our docs here 📚
🪶 All-In-One AI Conversations with LibreChat
LibreChat is a self-hosted AI chat platform that unifies all major AI providers in a single, privacy-focused interface.
Beyond chat, LibreChat provides AI Agents, Model Context Protocol (MCP) support, Artifacts, Code Interpreter, custom actions, conversation search, and enterprise-ready multi-user authentication.
Open source, actively developed, and built for anyone who values control over their AI infrastructure.
🌐 Resources
GitHub Repo:
- RAG API: github.com/danny-avila/rag_api
- Website: github.com/LibreChat-AI/librechat.ai
Other:
- Website: librechat.ai
- Documentation: librechat.ai/docs
- Blog: librechat.ai/blog
📝 Changelog
Keep up with the latest updates by visiting the releases page and notes:
⚠️ Please consult the changelog for breaking changes before updating.
⭐ Star History
✨ Contributions
Contributions, suggestions, bug reports and fixes are welcome!
For new features, components, or extensions, please open an issue and discuss before sending a PR.
If you'd like to help translate LibreChat into your language, we'd love your contribution! Improving our translations not only makes LibreChat more accessible to users around the world but also enhances the overall user experience. Please check out our Translation Guide.
💖 This project exists in its current state thanks to all the people who contribute
🎉 Special Thanks
We thank Locize for their translation management tools that support multiple languages in LibreChat.