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* 🗄️ fix: Gate Request-Scoped MCP Servers Out of Persistent Tool Cache PR #13626 established that request-scoped MCP servers (runtime OPENID/GRAPH/BODY placeholders) must not use the persistent 12h tool cache, but only gated three of five touchpoints. The panel endpoint still back-filled the cache and the OAuth callback still wrote to it, while agent loading read those entries ungated — pinning ephemeral model-spec/agent toolsets to stale definitions for up to 12h. Centralize the invariant in createMCPToolCacheService: a getServerConfig resolver dep gates both writers and a new service-owned getMCPServerTools read, so every current and future caller is covered. Callers that already hold the parsed config pass it to skip resolution; the per-call skipCache flag and duplicated call-site gates are removed in favor of the single config-based mechanism. Resolution failures fail open to preserve prior behavior. * 🩹 fix: Address Codex Review on Cache Gating - Repair getCachedTools.spec.js, which destructured the relocated getMCPServerTools directly from the module; its coverage now lives in the service-level tools.spec.ts. - Resolve the merged (Config-tier-aware) server config in the OAuth callback before writing tool definitions, so the cache gate detects request-scoped servers supplied via admin Config overlays that the base registry lookup cannot see. - Discover tools actively for request-scoped servers in the panel endpoint via ephemeral reinitialization: such servers have no stored app/user connections, so the previous getServerToolFunctions fallback returned an empty toolset once the cache read was gated. * 🧵 fix: Address Second Codex Review on Cache Gating - Resolve the merged server config before the OAuth callback reconnects, so the connection itself uses Config-tier overlays rather than only the subsequent cache write. - Pass Config-tier candidates into the panel's request-scoped discovery, matching the reinitialize route: reinitMCPServer forwards configServers (not the provided serverConfig) to its OAuth discovery fallback. - Document the accepted read-path trade-off: the gate resolver sees base configs only, all writers pass merged configs, so a pre-gating or overlay-divergent entry survives at most one cache TTL. * 🚏 chore: Rework Cache Gating for BODY-Only Request Scoping After #13673 narrowed requiresEphemeralUserConnection to BODY placeholders, the central gate follows the predicate unchanged, but the panel's active discovery no longer serves a purpose: the only remaining request-scoped class cannot connect outside a chat turn, so the reinitialization attempt would always fail at the missing-body check. Remove that path; OpenID/Graph servers are persistent user-scoped again and flow through the stored-connection and cache lookups as before. Flip test fixtures that used OPENID placeholders to denote request-scoped configs over to BODY placeholders. * 🪟 fix: Check Config Overlays in Agent-Loading Cache Reads The cache service's registry resolver sees only base YAML/DB configs, so a BODY placeholder introduced by a request-tier Config overlay was invisible to the gate on the agent-loading read path: model-spec and ephemeral-agent expansion could read a leftover persistent entry and pin stale concrete tool names instead of the mcp_all fresh-discovery path. Check the raw overlay candidate inline in loadEphemeralAgent and loadAddedAgent — a pure placeholder scan with no extra IO — and skip the cache read when the overlay makes the server request-scoped. Widen UserScopedConnectionConfig so raw (pre-inspection) configs qualify for the scoping predicates, which only check key presence. * 🧪 test: Guard Run-Scoped MCP Definition Handoff Boundaries The original ClickHouse breaker storm regressed precisely at field pass-through boundaries that unit tests of each end could not see: initializeAgent dropping mcpAvailableTools from its destructure, and the agent tool context losing it on the way into ON_TOOL_EXECUTE. Add direct guards on both hops: the loadTools result must surface on the initialized agent, and the captured toolExecuteOptions closure must forward it to loadToolsForExecution.
LibreChat
English · 中文
✨ Features
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🖥️ UI & Experience inspired by ChatGPT with enhanced design and features
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🤖 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
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🔦 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
- Skills: Create reusable
SKILL.mdinstruction bundles for manual, automatic, or always-on agent workflows - Subagents: Delegate focused work to isolated child agent runs with their own context windows
- 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:
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🔍 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 →
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🪄 Generative UI with Code Artifacts:
- Code Artifacts allow creation of React, HTML, and Mermaid diagrams directly in chat
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🎨 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
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💾 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 🗃️
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🌎 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 S3 with CloudFront for stable media links, edge delivery, signed cookies, and secured downloads
- 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.