[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-73713":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":14,"stars7d":17,"stars30d":18,"stars90d":16,"forks30d":16,"starsTrendScore":19,"compositeScore":20,"rankGlobal":10,"rankLanguage":10,"license":21,"archived":22,"fork":22,"defaultBranch":23,"hasWiki":22,"hasPages":22,"topics":24,"createdAt":10,"pushedAt":10,"updatedAt":45,"readmeContent":46,"aiSummary":47,"trendingCount":16,"starSnapshotCount":16,"syncStatus":48,"lastSyncTime":49,"discoverSource":50},73713,"archestra","archestra-ai\u002Farchestra","archestra-ai","Enterprise AI Platform with guardrails, MCP registry, gateway & orchestrator","https:\u002F\u002FArchestra.AI",null,"TypeScript",3819,998,11,76,0,61,167,33,111,"GNU Affero General Public License v3.0",false,"main",[25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44],"a2a","a2a-mcp","acp","agent","ai","chatgpt","chatgpt-api","claude","deepseek","gemini","k8s","mcp","mcp-client","mcp-gateway","mcp-host","mcp-server","mcp-servers","mcp-tools","openai","runtime","2026-06-12 04:01:10","# MCP-native Secure AI Platform\n\nSimplify AI usage in your company, providing user-friendly MCP toolbox, observability and control built on a strong security foundation.\n\n\u003Cdiv align=\"center\">\n\n[![License](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Flicense\u002Farchestra-ai\u002Farchestra)](LICENSE)\n\u003Cimg alt=\"GitHub commit activity\" src=\"https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fcommit-activity\u002Fm\u002Farchestra-ai\u002Farchestra\"\u002F>\n\u003Cimg alt=\"Github Last Commit\" src=\"https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Flast-commit\u002Farchestra-ai\u002Farchestra\"\u002F>\n[![Contributors](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fcontributors\u002Farchestra-ai\u002Farchestra)](https:\u002F\u002Fgithub.com\u002Farchestra-ai\u002Farchestra\u002Fgraphs\u002Fcontributors)\n\n\u003Cp align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fwww.archestra.ai\u002Fdocs\u002Fplatform-quickstart\">Getting Started\u003C\u002Fa>\n  - \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Farchestra-ai\u002Farchestra\u002Freleases\">Releases\u003C\u002Fa>\n  - \u003Ca href=\"https:\u002F\u002Farchestra.ai\u002Fjoin-slack\">Slack Community\u003C\u002Fa>\n\u003C\u002Fp>\n\u003C\u002Fdiv>\n\n_For Platform teams:_\n\n- Mitigate MCP chaos, move MCP servers from individual machines to a centralized orchestrator\n- Manage how MCP access data and credentials usage\n- Mitigate data exfiltration risks\n- Manage AI costs\n- AI Observability\n\n_For Developers:_\n\n- Deploy your MCP servers org-wide\n- Build and deploy agents without worrying about security\n\n_For Management:_\n\n- Bring 1-click MCP adoption to the whole organization for technical and non-technical users\n- Reduce AI costs up to 96%\n- Get full visibility on AI adoption, usage and data access\n\n## 🚀 Quickstart with docker\n\n```\ndocker pull archestra\u002Fplatform:latest;\ndocker run -p 9000:9000 -p 3000:3000 \\\n  -e ARCHESTRA_QUICKSTART=true \\\n  -v \u002Fvar\u002Frun\u002Fdocker.sock:\u002Fvar\u002Frun\u002Fdocker.sock \\\n  -v archestra-postgres-data:\u002Fvar\u002Flib\u002Fpostgresql\u002Fdata \\\n  -v archestra-app-data:\u002Fapp\u002Fdata \\\n  archestra\u002Fplatform;\n```\n\n[Full Quickstart Guide →](https:\u002F\u002Farchestra.ai\u002Fdocs\u002Fplatform-quickstart)\n\n## 👩‍💻 ChatGPT-like chat with MCPs\n\n🎁 with private company-wide prompt registry!\n\n\u003Cdiv align=\"center\">\n\u003Cimg src=\"docs\u002Fassets\u002Fchat.webp\" alt=\"ChatGPT-like chat\" \u002F>\n\u003C\u002Fdiv>\n\n## 📋 Private MCP registry with governance\n\nAdd MCPs to your private registry to share them with your team: self-hosted and remote, self-built and third-party.\n\n[Learn more about Private MCP Registry →](https:\u002F\u002Farchestra.ai\u002Fdocs\u002Fplatform-private-registry)\n\n\u003Cdiv align=\"center\">\n\u003Cimg src=\"docs\u002Fassets\u002Fmcp-registry.webp\" alt=\"MCP Registry\" \u002F>\n\u003C\u002Fdiv>\n\n## ☁️ Kubernetes-native MCP orchestrator\n\nRun MCP servers in kubernetes, managing their state, API keys, OAuth.\n\n[Learn more about MCP Orchestrator →](https:\u002F\u002Farchestra.ai\u002Fdocs\u002Fplatform-orchestrator)\n\n\u003Cdiv align=\"center\">\n\u003Cimg src=\"docs\u002Fassets\u002Forchestrator.webp\" alt=\"MCP Orchestrator\" \u002F>\n\u003C\u002Fdiv>\n\n## 📚 RAG Knowledge Base\n\nBuilt-in retrieval-augmented Knowledge Base — no external vector database or separate retrieval service required.\n\n[Learn more about Knowledge Base →](https:\u002F\u002Farchestra.ai\u002Fdocs\u002Fplatform-knowledge-bases)\n\n\u003Cdiv align=\"center\">\n\u003Cimg src=\"docs\u002Fassets\u002Fautomated_screenshots\u002Fplatform-knowledge-bases_chat-with-citations.webp\" alt=\"RAG Knowledge Base\" \u002F>\n\u003C\u002Fdiv>\n\n## 🤖 Security sub-agents\n\nIsolating dangerous tool responses from the main agent to prevent prompt injections.\n\n[Learn more about Dual LLM →](https:\u002F\u002Farchestra.ai\u002Fdocs\u002Fplatform-dual-llm)\n\n\u003Cdiv align=\"center\">\n\u003Cimg src=\"docs\u002Fassets\u002Fdual-llm.webp\" alt=\"Dual-LLM sub-agent\" \u002F>\n\u003C\u002Fdiv>\n\n## 🚫 Non-probabalistic security to prevent data exfiltration\n\nModels could consume prompt injections via MCP uncontrollably (read your inbox, read your GitHub issues, read your customer's inquiries) and follow them resulting in data exfiltration.\n\n[Learn more about Tool Guardrails →](https:\u002F\u002Farchestra.ai\u002Fdocs\u002Fplatform-ai-tool-guardrails) | [The Lethal Trifecta →](https:\u002F\u002Farchestra.ai\u002Fdocs\u002Fplatform-lethal-trifecta)\n\nLive demo of archestra security engine preventing data leak from the private GitHub repo to the public repo:\n[![Archestra Demo](https:\u002F\u002Fimg.youtube.com\u002Fvi\u002FSkmluS-xzmM\u002F0.jpg)](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=SkmluS-xzmM&t=2155s)\n\nRead more: [Simon Willison](https:\u002F\u002Fsimonwillison.net\u002F2025\u002FJun\u002F16\u002Fthe-lethal-trifecta\u002F), [The Economist](https:\u002F\u002Fwww.economist.com\u002Fleaders\u002F2025\u002F09\u002F25\u002Fhow-to-stop-ais-lethal-trifecta)\n\nExamples of hacks:\n[ChatGPT](https:\u002F\u002Fsimonwillison.net\u002F2023\u002FApr\u002F14\u002Fnew-prompt-injection-attack-on-chatgpt-web-version-markdown-imag\u002F) (April 2023), [ChatGPT Plugins](https:\u002F\u002Fsimonwillison.net\u002F2023\u002FMay\u002F19\u002Fchatgpt-prompt-injection\u002F) (May 2023), [Google Bard](https:\u002F\u002Fsimonwillison.net\u002F2023\u002FNov\u002F4\u002Fhacking-google-bard-from-prompt-injection-to-data-exfiltration\u002F) (November 2023), [Writer.com](https:\u002F\u002Fsimonwillison.net\u002F2023\u002FDec\u002F15\u002Fwritercom-indirect-prompt-injection\u002F) (December 2023), [Amazon Q](https:\u002F\u002Fsimonwillison.net\u002F2024\u002FJan\u002F19\u002Faws-fixes-data-exfiltration\u002F) (January 2024), [Google NotebookLM](https:\u002F\u002Fsimonwillison.net\u002F2024\u002FApr\u002F16\u002Fgoogle-notebooklm-data-exfiltration\u002F) (April 2024), [GitHub Copilot Chat](https:\u002F\u002Fsimonwillison.net\u002F2024\u002FJun\u002F16\u002Fgithub-copilot-chat-prompt-injection\u002F) (June 2024), [Google AI Studio](https:\u002F\u002Fsimonwillison.net\u002F2024\u002FAug\u002F7\u002Fgoogle-ai-studio-data-exfiltration-demo\u002F) (August 2024), [Microsoft Copilot](https:\u002F\u002Fsimonwillison.net\u002F2024\u002FAug\u002F14\u002Fliving-off-microsoft-copilot\u002F) (August 2024), [Slack](https:\u002F\u002Fsimonwillison.net\u002F2024\u002FAug\u002F20\u002Fdata-exfiltration-from-slack-ai\u002F) (August 2024), [Mistral Le Chat](https:\u002F\u002Fsimonwillison.net\u002F2024\u002FOct\u002F22\u002Fimprompter\u002F) (October 2024), [xAI's Grok](https:\u002F\u002Fsimonwillison.net\u002F2024\u002FDec\u002F16\u002Fsecurity-probllms-in-xais-grok\u002F) (December 2024), [Anthropic's Claude iOS app](https:\u002F\u002Fsimonwillison.net\u002F2024\u002FDec\u002F17\u002Fjohann-rehberger\u002F) (December 2024), [ChatGPT Operator](https:\u002F\u002Fsimonwillison.net\u002F2025\u002FFeb\u002F17\u002Fchatgpt-operator-prompt-injection\u002F) (February 2025), [Notion 3.0](https:\u002F\u002Fwww.codeintegrity.ai\u002Fblog\u002Fnotion) (September 2024).\n\n## 💰 Cost monitoring, limits and dynamic optimization\n\nPer-team, per-agent or per-org cost monitoring and limitations. Dynamic optimizer allows to reduce cost up to 96% by simply switching to cheaper models automatically for simpler tasks.\n\n[Learn more about Costs & Limits →](https:\u002F\u002Farchestra.ai\u002Fdocs\u002Fplatform-costs-and-limits)\n\n\u003Cdiv align=\"center\">\n\u003Cimg src=\"docs\u002Fassets\u002Fcost.webp\" alt=\"Cost & Limits\" \u002F>\n\u003C\u002Fdiv>\n\n## 📊 Observability\n\nMetrics, traces and logs allowing to come to a conclusion about per-org, per-agent and per-team token and tool usage, and performance.\n\n[Learn more about Observability →](https:\u002F\u002Farchestra.ai\u002Fdocs\u002Fplatform-observability)\n\n\u003Cdiv align=\"center\">\n\u003Cimg src=\"docs\u002Fassets\u002Fobservability.webp\" alt=\"Observability\" \u002F>\n\u003C\u002Fdiv>\n\n## 👍 Ready for production\n\n1. ✅ Lightning fast, 45ms at 95p: [Performance & Latency benchmarks →](https:\u002F\u002Farchestra.ai\u002Fdocs\u002Fplatform-performance-benchmarks)\n2. ✅ [Terraform provider →](https:\u002F\u002Fgithub.com\u002Farchestra-ai\u002Fterraform-provider-archestra)\n3. ✅ [Helm Chart →](https:\u002F\u002Farchestra.ai\u002Fdocs\u002Fplatform-deployment#helm-deployment-recommended-for-production)\n\n## 🤝 Contributing\n\nWe welcome contributions from the community!\n\n- [Contribution Guidelines →](https:\u002F\u002Farchestra.ai\u002Fdocs\u002Fcontributing)\n- [Developer Quickstart →](https:\u002F\u002Farchestra.ai\u002Fdocs\u002Fplatform-developer-quickstart)\n- [Security & Bug Bounty →](https:\u002F\u002Farchestra.ai\u002Fdocs\u002Fsecurity)\n\nThank you for contributing and continuously making \u003Cb>Archestra\u003C\u002Fb> better, \u003Cb>you're awesome\u003C\u002Fb> 🫶\n\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Farchestra-ai\u002Farchestra\u002Fgraphs\u002Fcontributors\">\n  \u003Cimg src=\"https:\u002F\u002Fcontrib.rocks\u002Fimage?repo=archestra-ai\u002Farchestra\" \u002F>\n\u003C\u002Fa>\n\n---\n\n\u003Cdiv align=\"center\">\n  \u003Cbr \u002F>\n  \u003Ca href=\"https:\u002F\u002Fwww.archestra.ai\u002Fblog\u002Farchestra-joins-cncf-linux-foundation\">\u003Cimg src=\".\u002Fdocs\u002Fassets\u002Flinux-foundation-logo.webp\" height=\"50\" alt=\"Linux Foundation\" \u002F>\u003C\u002Fa>\n        \n  \u003Ca href=\"https:\u002F\u002Fwww.archestra.ai\u002Fblog\u002Farchestra-joins-cncf-linux-foundation\">\u003Cimg src=\".\u002Fdocs\u002Fassets\u002Fcncf-logo.webp\" height=\"50\" alt=\"CNCF\" \u002F>\u003C\u002Fa>\n\u003C\u002Fdiv>\n","Archestra 是一个为企业提供安全AI平台的解决方案，内置MCP注册表、网关和编排器。该项目采用TypeScript开发，核心功能包括简化企业内部AI工具的使用与管理、增强数据安全性和成本控制能力，并提供强大的可观测性。特别适用于需要集中管理和优化多云平台（MCP）资源的企业环境，支持一键式部署AI服务，既适合技术团队也方便非技术人员快速上手。此外，它还提供了私有MCP注册表、Kubernetes原生编排器以及集成的知识库等功能，进一步增强了系统的灵活性与安全性。",2,"2026-06-11 03:47:04","high_star"]