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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
3758380c61
* 🔌 fix: Follow 307/308 redirects in MCP streamable HTTP transport Some MCP servers (e.g. Coda) return 308 Permanent Redirect to route doc-scoped tool calls to a different endpoint path. The fetch wrapper used `redirect: 'manual'` for SSRF protection, which silently dropped these redirects and caused tool calls to fail with empty error bodies. Follow 307/308 redirects (method-preserving per RFC 7538) up to a depth of 5. SSRF safety is preserved because the same undici Agent with its SSRF-safe connect function validates redirect targets. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * 🛡️ fix: Harden MCP 307/308 redirect handling against SSRF and credential leaks - Validate every redirect target against `resolveHostnameSSRF` so allowlist deployments (which disable connect-time SSRF protection) still block hops to private/reserved IPs. - Strip `Authorization`, `Cookie`, `mcp-session-id`, and any user-injected headers when a 307/308 crosses an origin boundary, mirroring browser/Fetch behavior so a redirecting MCP server can't exfiltrate credentials. - Cancel the intermediate response body before each next hop so undici can reuse pooled sockets rather than holding them until GC. - Restructure redirect test helpers to be same-origin (matching real-world Coda-style routing), drop dead setup code, fix the misleading "5 hops successfully" test, and add coverage for SSRF-blocked redirects, cross- origin credential stripping, and same-origin credential preservation. * 🛡️ fix: Also strip `serverConfig.headers` on cross-origin MCP redirects Previously only runtime `setRequestHeaders` keys were treated as secret on a 307/308 cross-origin hop. API keys baked into `serverConfig.headers` (passed through `requestInit.headers` at transport construction time) survived stripping, so a malicious MCP endpoint could exfiltrate them by returning a cross-origin `Location`. Pass the configured header keys through to `createFetchFunction` so both runtime and config secrets are stripped. The cross-origin credential test now also configures `serverConfig.headers` to lock in this behavior. * 🧹 chore: Tighten MCP redirect-stripping coverage and helper duplication - Add `proxy-authorization` to the cross-origin forbidden header set so a forward-proxy credential header would also be stripped on a cross-origin hop, matching the Fetch-spec list. - Strengthen the cross-origin credential test with positive assertions that benign protocol headers (`accept`, `content-type`) survive the hop, so a regression that strips everything indiscriminately would now fail. - Extract the duplicated MCP request handler / session-teardown logic from three test helpers into shared `createMCPRequestHandler` and `closeMCPSessions` utilities. * 🛠️ fix: Handle `Request` inputs in MCP `customFetch` URL derivation `customFetch` is typed to accept `UndiciRequestInfo` (`string | URL | Request`), but `Request.prototype.toString()` returns `"[object Request]"`. The previous implementation derived `originalOrigin` and the redirect base via `url.toString()`, so a `Request` input would throw inside `new URL(...)` before any network call — a regression even when no redirect was involved. Add a `getRequestUrlString` helper that extracts the URL string for all three shapes, track the URL string alongside the fetch input through the redirect loop, and add parameterized tests that exercise `customFetch` with each shape. * 🛠️ fix: Don't override `Request` input headers in MCP `buildFetchInit` Previously `buildFetchInit` always set `headers` on the returned init — even when neither `init.headers` nor runtime headers contributed anything. Passing `headers: {}` to `undiciFetch` overrides the headers carried on a `Request` input (auth tokens, MCP session, protocol negotiation), so Request-based wrappers could fail authentication even without a redirect in play. Skip the `headers` override entirely when there is nothing to merge. Adds a regression test that supplies `Authorization` and a custom header on the `Request` itself and asserts both reach the target server. * 🛠️ fix: Preserve `Request` method/body across MCP redirects + guard cross-origin strip Two regressions surfaced by extending `customFetch` to accept `Request` inputs: 1. **307/308 method/body loss.** The redirect loop switches `url` to the new `Location` string, but the original `Request`'s method and body stayed bound to the (now-discarded) `Request` object. A redirected POST silently became a GET with no payload — the exact behavior the method-preserving codes are designed to prevent. Added a `resolveFetchInput` helper that runs once at the top of `customFetch`, extracts a `Request`'s method/body/headers into the shared init, and buffers the body via `arrayBuffer()` so 307/308 retries can replay it. 2. **Cross-origin strip crashed on absent headers.** After the previous fix that stopped `buildFetchInit` from setting `headers: {}`, `currentInit.headers` could legitimately be `undefined`. The cross-origin branch read it as a `Record` and called `Object.entries` on `undefined`, throwing `TypeError`. Guard the branch on `currentInit.headers != null` — when there are no headers there is nothing to strip. Adds two regression tests: a POST-with-body `Request` that 308-redirects cross-origin (asserts both method and body survive) and a no-headers cross-origin redirect (asserts the strip path no longer crashes). * 🛠️ fix: Forward `Request.signal` through MCP `customFetch` normalization `resolveFetchInput` was copying method/body/headers off a `Request` input but dropping `Request.signal` on the floor, so a caller that wired an `AbortController` onto the `Request` for cancellation/timeouts lost that wiring as soon as we re-shaped the input into the `(string, init)` pair used by the redirect loop. Subsequent aborts no longer reached the in-flight fetch — a regression from the pre-PR code, which forwarded the original `Request` directly to undici. Forward the signal alongside method/body/headers, with explicit `init.signal` still winning per Fetch-spec semantics. Regression test aborts a controller before calling \`customFetch\` with the wired `Request` and asserts the call rejects. * 🧪 test: Pin URL.origin contract for protocol-downgrade redirect handling Audit follow-up. The cross-origin strip path keys off `targetUrl.origin !== originalOrigin`, and `URL.origin` is defined as `scheme + "://" + host + ":" + port`, so a same-host `https → http` redirect produces a different origin and trips the strip path through the existing logic — no separate code path needed. Pin that contract with a small unit test so a future change to URL semantics (or a refactor that swaps in a different comparison) doesn't silently regress protocol-downgrade stripping. Standing up a TLS fixture (self-signed cert, undici skip-verify, etc.) just to re-prove the URL spec is wasted complexity. --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: Danny Avila <danny@librechat.ai> |
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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
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- 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
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💬 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
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🧠 Reasoning UI:
- Dynamic Reasoning UI for Chain-of-Thought/Reasoning AI models like DeepSeek-R1
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🎨 Customizable Interface:
- Customizable Dropdown & Interface that adapts to both power users and newcomers
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- 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
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🗣️ Speech & Audio:
- Chat hands-free with Speech-to-Text and Text-to-Speech
- Automatically send and play Audio
- Supports OpenAI, Azure OpenAI, and Elevenlabs
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📥 Import & Export Conversations:
- Import Conversations from LibreChat, ChatGPT, Chatbot UI
- Export conversations as screenshots, markdown, text, json
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🔍 Search & Discovery:
- Search all messages/conversations
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👥 Multi-User & Secure Access:
- Multi-User, Secure Authentication with OAuth2, LDAP, & Email Login Support
- Built-in Moderation, and Token spend tools
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⚙️ Configuration & Deployment:
- Configure Proxy, Reverse Proxy, Docker, & many Deployment options
- Use completely local or deploy on the cloud
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📖 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.