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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
29b3e2ef3e
* fix: Fetch MCP Instructions from the First Live Connection Startup inspection intentionally defers servers that need per-user or runtime context, including OAuth/OBO, custom variables, user API keys, runtime placeholders, and startup-disabled servers. An enabled serverInstructions declaration therefore never resolves to text during inspection, even though the first live connection already has the instructions from the initialize response. Backfill resolvedInstructions from that connection through an identity-preserving YAML cache patch. Preserve updatedAt so live connections do not become stale, and globally invalidate the tenant-scoped read-through caches because YAML entries are shared across tenants. Literal instruction strings continue to win. Scope remains YAML-tier servers. Config-overlay servers are keyed by config hash, and DB-backed user servers need a separate identity-preserving write through mongoose timestamps and credential sanitization. * fix: Surface per-identity MCP instruction divergence `resolvedInstructions` is a single field on a config shared by every user of the server, and for a startup-deferred server the text now comes from one user's authenticated connection. That is exact for a server advertising one static block, but a server that tailors instructions per identity cannot be represented by it. Rather than let the stored copy churn per connection — each write invalidates the read-through cache globally, and the model context would vary by whoever connected last — keep the first text and log the divergence, so the assumption is diagnosable instead of silent. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01SxKWxwqxAGckYpRsYTqx3F * perf: Skip MCP instruction backfill for non-YAML tiers `setResolvedInstructions` writes only the YAML tier, so a config-overlay, user, or plugin server reached it, spent a cache round-trip — a network hop under Redis — and was refused. That repeated on every connection creation, because the refusal leaves `resolvedInstructions` unset and nothing memoizes the outcome. Gate on the existing `isUserSourced`/`isPluginSourced` predicates plus an explicit `config` check. An unset source still proceeds: it predates per-tier stamping and the registry resolves it by name. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01SxKWxwqxAGckYpRsYTqx3F * test: Pin the MCP instruction context read path Every existing assertion read back through `getServerConfig`, but `MCPManager.getInstructions` resolves instructions from `getAllServerConfigs`, which is served by a different read-through cache. A backfill that invalidated only the per-server cache would pass the suite and still leave the reported bug unfixed. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01SxKWxwqxAGckYpRsYTqx3F * fix: Refuse MCP instruction backfill from mismatched configs Self-review findings on the backfill, both in the shared-copy write: A config-tier override shadowing a YAML base keeps the base's 'yaml' source tag (`overlaySource`), so the connection manager's tier guard cannot see it, and instructions fetched from a tenant's overridden endpoint would be patched into the shared global YAML entry — reaching every other tenant's model context and persisting after the override is removed. `setResolvedInstructions` now takes the config the delivering connection was created from and compares it field-wise against the stored entry over ADMIN_CONFIGURABLE_FIELDS, refusing on mismatch. Field-wise rather than whole-object, since inspector-derived fields legitimately differ. The skip condition also only refused *identical* text, so a connection built from a stale read-through snapshot (resolvedInstructions still unset) could overwrite already-stored different text — violating the documented first-write-wins invariant and re-triggering global cache invalidation per divergence. The condition is now `!= null`. Documented the aggregate-key cross-instance write race alongside its existing tolerance for `reinspectServer`: the backfill patch fires at most once per server per registry lifetime, and the atomic-write upgrade (hash fields or Lua CAS) is the follow-up that closes the race for every writer at once. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01SxKWxwqxAGckYpRsYTqx3F * fix: Scope deferred MCP instructions safely * fix: Narrow optional Keyv namespace in Redis store detection Keyv types `namespace` as `string | undefined`, so passing it straight into `FORCED_IN_MEMORY_CACHE_NAMESPACES?.includes(...)` fails `tsc --noEmit` in both cache classes — tsdown builds do not catch it, but the TypeScript type checks CI job runs tsc and would. An unset namespace (never the case after construction) now reads as not Redis-backed, which falls back to the guarded non-Lua path. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01SxKWxwqxAGckYpRsYTqx3F * fix: Harden the shared-instruction gate and CAS the patch Codex round two, both verified before fixing: A configured `oauth` block slips the backfill gate whenever `requiresOAuth` is not literally true. The inspector stamps `requiresOAuth = false` on every `startup: false` server without consulting `oauth`, so the stamped population connects bare and fetches anonymously — but the gate's safety rested entirely on that stamp: a config reaching the manager unstamped gets OAuth machinery armed (`isOAuthServer` treats `oauth != null` as OAuth) while `requiresUserScopedConnection` waves it through. The gate now rejects `oauth`/`oauth_headers` outright; genuinely static servers carry neither. The registry validates config identity against a snapshot that can lag by the cache TTL, while the Lua patch checked only that `resolvedInstructions` was unset — so a replica could validate against an old entry, another replica replace it, and the patch land instructions on the replacement. `patch` now takes the validated entry's `updatedAt` and both Lua scripts (and the in-memory and fallback paths) refuse when the stored entry no longer matches: identity validation and the write are one compare-and-set. Both guards verified red-without-fix; suite 36/36. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01SxKWxwqxAGckYpRsYTqx3F * fix: Loosen apiKey on the scoping config and sort imports CI caught two things local gates filtered past: `UserScopedConnectionConfig` gained `apiKey` on the strict Pick side, but raw (pre-inspection) configs carry an optional `apiKey.source` — exactly what the type's loosened intersection exists for — so `agents/initialize.ts` stopped compiling. The gate only reads `apiKey?.source`, so the loosened shape is sufficient and the TypeScript type checks job goes green again. The `canBackfillSharedServerInstructions` import landed unsorted in UserConnectionManager.ts, failing the changed-file import-sort gate. Verified with a full `tsc --noEmit` error-list diff against clean dev (zero branch-only errors) rather than per-directory counts, which is how the initialize.ts error slipped local verification. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01SxKWxwqxAGckYpRsYTqx3F * fix: Make MCP aggregate writes atomic * test: Fix Redis aggregate spy assertion * fix: Reject placeholder-bearing admin keys from shared backfill Codex round three P1, verified end-to-end before fixing: processMCPEnv injects an admin `apiKey.key` into the request headers (env.ts:448) BEFORE header values get per-user placeholder resolution (env.ts:478), so a key like `{{LIBRECHAT_OPENID_ACCESS_TOKEN}}` makes the connection identity-scoped — while `placeholderBearingFields` never inspects `apiKey.key` and the gate rejected only `source: 'user'`. Instructions fetched under one user's identity could then be stored for everyone. The gate now scans the admin key value with the same runtime-placeholder predicate. Kept narrow deliberately: widening `placeholderBearingFields` itself would change `requiresUserScopedConnection` for every caller — connection pooling included — which is its own decision. Static admin keys still backfill (positive control test); both new refusal tests verified red without the gate change. Suite 39/39. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01SxKWxwqxAGckYpRsYTqx3F * refactor: Drop gate term covered by placeholder-bearing apiKey |
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LibreChat
English · 中文
🚀 What's New in v0.8.8-rc1
- Agent run control: Interrupt or steer an Agent mid-run, queue follow-up messages, and reclaim, edit, or escalate pending steers.
- Human-in-the-loop Agents: Agents stream question progress, ask up to four related questions in one form, pause for input or tool approval, and resume.
- Unified Agent Builder: A redesigned Tools marketplace brings together Skills, MCP, Code Interpreter, orchestration, Programmatic Tool Calling, model-spec controls, and per-tool background and intent settings.
- Readable Agent activity: Generated activity-group headers, parent phase summaries, and live tool intent labels make long reasoning and tool runs easier to scan.
- Code Interpreter workflows: Code and shell tools can run in the background, sandbox images return as viewable artifacts, and highly experimental stateful sessions can reuse prewarmed conversation workspaces.
- Agent extensibility: Experimental Agent Plugins can bundle deployment Skills, MCP servers, and opt-in command hooks, while explicit subagents initialize only when selected.
- Memory, context, and identity: Agents can manage memory with optional per-agent isolation, expose support contacts safely, and show a more faithful Context Usage gauge.
- Sharing and files: Shared conversations show a badge and update at a stable URL, while signed-in viewers can continue them as personal copies.
- Artifact workflows: Open previews fullscreen, work with PowerPoint
.potxtemplates across upload, search, and code execution, upload shell scripts across common MIME variants, export Mermaid diagrams as SVG or PNG, and download original Office files from the artifact panel. - Models and reasoning: Added GPT-5.6 with Responses API reasoning controls, Claude Opus 5 and Sonnet 5, Gemini 3.7 and 3.6 Flash, and Gemini 3.5 Flash-Lite.
- Langfuse observability: Configure encrypted Langfuse connections in-app, let authorized admins open sampled sessions directly, optionally fan out traces by tenant, and suppress central export per run.
- Administration and security: Delegate config sections, encrypt registered secrets, enforce SSRF checks for speech, OCR, and web tools, and generate unique temporary credentials when secrets are blank.
- Messages and navigation: Right-aligned user turns, unified multi-part editing, full-message copy, a dock-style message rail, virtualized search, smooth streaming, and faster Agent startup.
- Streaming and tool reliability: Adaptive provider smoothing, Redis delta batching, dynamic MCP tool refresh, parsed MCP response media types, runtime OAuth recovery, and Agent stream circuit breakers improve long-running workflows.
- Deployment and reliability: Added configurable HTTP timeouts, Amazon DocumentDB 5.0+ support, low-noise Redis and browser observability, and a rolling-upgrade-safe generation protocol.
Read the full v0.8.8-rc1 changelog.
✨ 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
- Open-Source & Self-Hostable: powered by ClickHouse/code-interpreter
-
🔦 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 - Agent Plugins: Experimentally bundle deployment Skills and MCP servers into startup-loaded packages
- 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:
-
🔍 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 create React, HTML, and Mermaid content directly in chat
- Open previews fullscreen and export Mermaid diagrams as SVG or PNG
-
🎨 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 🗃️
-
🌎 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
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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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🎛️ Admin Panel:
- Browser-based UI to manage users, groups, roles, and configuration overrides
- Edit settings and per-role/group permissions live, without redeploying
- Bundled with the Docker Compose stacks for one-command setup
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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
-
📖 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.