{"data":{"slug":"nduckmink-arkon","name":"arkon","tagline":"Self-hosted enterprise AI knowledge hub and MCP server for secure RAG contexts and policy management.","github_url":"https://github.com/nduckmink/arkon","owner":"nduckmink","repo":"arkon","owner_avatar_url":"https://avatars.githubusercontent.com/u/250913026?v=4","primary_language":"Python","stars":1454,"forks":291,"topics":["enterprise-ai","knowledge-base-embeddings","knowledge-based-systems","knowledge-bases","llm-wiki-personal-knowledge-base","mcp","mcp-server","model-context-protocol","organizational-knowledge","rag","self-hosted","wiki"],"archived":false,"github_pushed_at":"2026-06-03T18:41:48+00:00","maintenance_label":"Slowing","stars_delta_30d":376,"url":"https://www.graphcanon.com/tools/nduckmink-arkon","markdown_url":"https://www.graphcanon.com/tools/nduckmink-arkon.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/nduckmink-arkon","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=nduckmink-arkon","description":"Arkon: Enterprise AI Knowledge Hub & MCP Server. Self-hosted knowledge base for teams to manage RAG contexts, access policies, and AI skills. Connect Claude and other LLMs via Model Context Protocol (MCP) for automated, secure organizational knowledge integration.","homepage_url":null,"license":"Other","open_issues":21,"watchers":17,"ai_summary":"Arkon is designed for teams to manage and integrate organizational knowledge with large language models through the Model Context Protocol (MCP). It provides self-hosting capabilities, allowing users to control access policies and AI skills within an enterprise setting.","readme_excerpt":"## 💻 Server Requirements\n\nArkon runs **7 Docker containers** (PostgreSQL + pgvector, Redis, MinIO, FastAPI API, 2 ARQ workers, Next.js frontend). The table below provides recommended configurations based on team size:\n\n| | **Starter** | **Team** | **Enterprise** |\n|---|:---:|:---:|:---:|\n| **Team size** | 1 – 20 | 20 – 100 | 100+ |\n| **vCPU** | 2 cores | 4 cores | 8+ cores |\n| **RAM** | 4 GB | 8 GB | 16+ GB |\n| **Storage** | 40 GB SSD | 100 GB SSD | 250+ GB NVMe SSD |\n| **OS** | Ubuntu 22.04+ / Debian 12+ | Ubuntu 22.04+ / Debian 12+ | Ubuntu 22.04+ / Debian 12+ |\n| **Use case** | Evaluation / small teams | Departmental deployment | Organization-wide rollout |\n\n> [!NOTE]\n> - **RAM** is the primary bottleneck — the MRP pipeline workers load large LLM context windows into memory during wiki compilation.\n> - **Storage** scales with your document corpus — pgvector indexes, MinIO file storage, and PostgreSQL WAL logs are the main consumers.\n> - All AI inference happens externally (Anthropic / Google / OpenAI APIs), so **GPU is not required**.\n> - A reverse proxy (Nginx / Caddy) with SSL is recommended for production. See [Setup Guide](docs/SETUP.md).\n\n---\n\n---\n\n## 🚦 Quick Start (Docker)\n\n> [!NOTE]\n> **Arkon is built for teams, not individuals.** If you're looking for a personal knowledge setup, [Obsidian](https://obsidian.md) + Claude Skills is a much simpler fit.\n>\n> **Not a tech person?** Skip the self-hosting hassle — reach out for a **free guided demo** tailored for your team. No config, no Docker, just a walkthrough of what Arkon can do for your organization.\n\n**Prerequisites:** Docker & Docker Compose, plus an API key from your preferred AI provider (Anthropic, Google, or OpenAI).\n\n1. **Clone the repository:**\n   ```shell\n   git clone https://github.com/nduckmink/arkon.git\n   cd arkon\n   ```\n\n2. **Configure environment:**\n   ```shell\n   cp .env.docker.example .env.docker\n   # Edit .env.docker - set SECRET_KEY, admin credentials, and Postgres/MinIO secrets\n   ```\n\n3. **Launch:**\n   ```shell\n   docker compose --env-file .env.docker up -d --build\n   ```\n\n4. Access the portal at `http://localhost:3119`, sign in as admin, then go to **Settings** to pick your embedding / LLM / vision models and paste API keys.\n\n→ See [Setup Guide](docs/SETUP.md) for development mode and the full env reference.\n\n---\n\n---\n\n## 📄 License\n\nArkon is licensed under the [PolyForm Internal Use License 1.0.0](LICENSE). Free for internal business operations; you may not offer Arkon as a service to third parties.\n\nFor enterprise support or custom integrations, please contact the maintainers.\n\n---\n\n**Keywords:** *Enterprise AI, Model Context Protocol, MCP Server, Knowledge Management System, Self-hosted RAG, AI Knowledge Base, Claude MCP, LLM Context Management, Open Source Wiki.*\n\n---","github_created_at":"2026-04-30T15:11:39+00:00","created_at":"2026-07-11T11:53:00.219301+00:00","updated_at":"2026-09-20T06:42:48.732189+00:00","categories":[{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"}],"tags":[{"slug":"enterprise-ai","name":"enterprise-ai"},{"slug":"knowledge-base-embeddings","name":"knowledge-base-embeddings"},{"slug":"model-context-protocol","name":"model-context-protocol"},{"slug":"rag","name":"rag"}],"trust":{"provenance":{"is_fork":false,"github_id":1225722703,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-20T03:56:02.532Z","maintenance":{"label":"Slowing","score":36,"methodology":"github_public_v1","releases_90d":0,"days_since_push":108,"last_release_at":"2026-06-01T11:49:06Z","stars_delta_30d":376,"open_issues_delta_30d":3},"security_summary":{"status":"no_manifest","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:53:01.327Z","medium_count":0,"scan_profile":"mcp_manifest","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-20T03:56:03.540Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-09-20T03:56:03.540Z","managed_saas":false},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-09-20T03:56:03.540Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-09-20T03:56:03.540Z"},"license_spdx":{"value":"Other","source":"github.license","observed_at":"2026-09-20T03:56:03.540Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When your team requires centralized control over access policies and the integration of organizational knowledge with large language models through the Model Context Protocol (MCP).","For enterprises that need to self-host their systems for security reasons, providing complete governance over AI skills and knowledge contexts within the company."],"when_not_to_use":["If you are looking for a platform that does not offer control over access policies or require external hosting solutions.","In scenarios where secure and enterprise-specific policy management for RAG contexts is unnecessary or impractical, favoring platforms with more open architectures."],"source":"enrich:decision_facts","observed_at":"2026-07-17T11:51:32.604Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Self-hosted AI knowledge hub and MCP server for secure RAG contexts tailored for enterprise environments."}]}}