Arkon
Self-hosted enterprise knowledge hub that compiles organizational docs into a structured wiki and serves it to AI clients via MCP with fine-grained access control.
README
Arkon - The Open-Source Enterprise AI Knowledge Hub & MCP Server
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<p align="center"> <img src="docs/assets/arkon.png" alt="Arkon" width="720"> </p>
Arkon is a self-hosted, enterprise-grade knowledge management layer that bridges organizational data and AI clients. It runs as a centralized MCP Server (Model Context Protocol), compiling your SOPs, policies, and internal docs into a structured, traceable knowledge wiki - then serving that wiki to Claude and other LLMs through a single permission-scoped endpoint.
π Why Arkon?
In most organizations, AI adoption is fragmented. Employees copy-paste documents into chatbots, producing inconsistent context, security risks, and duplicated work.
Arkon treats AI as a managed organizational resource. Every employee gets the right context, automatically and securely - filtered by their department and role.
<p align="center"> <img src="docs/assets/how-arkon-works.png" alt="How Arkon Works" width="720"> </p>
β¨ Key Features
π§ Intelligent Knowledge Wiki - the MRP Pipeline
Unlike a vector database that just chunks and indexes, Arkon's MRP pipeline (Map β Reduce β Plan-review β Refine β Verify β Commit) actually compiles documents into a coherent wiki of interlinked pages.
- Plan review before write: every ingestion produces a human-reviewable plan listing which wiki pages will be created or updated. Editors can regenerate the plan with feedback before any page is written.
- Page merge instead of overwrite: when a new source touches an existing wiki page, content is LLM-merged so prior knowledge is never lost.
- Traceable claims: every page records the source documents it was compiled from.
- Image-aware: vision captions are baked into source text before compilation, so wiki pages reference the right images in the right places.
- Resumable: drafts persist mid-pipeline; a crashed run resumes without re-doing the expensive LLM work.
π Wiki Browser & Knowledge Graph
- Three-panel layout: page tree, content, backlinks & outlinks.
- Full-text + semantic (pgvector) search.
- Interactive knowledge graph visualization (per-scope or global).
- Wikilink-style cross-references between pages.
- Version history and rollback on every page.
- Draft proposal β editor review β approval workflow.
<p align="center"> <img src="docs/assets/arkon-wiki-ui.png" alt="Arkon Wiki Browser UI β three-panel knowledge base with page tree, content viewer, and knowledge graph" width="720"> </p>
π’ Department & Global Scopes
Precise context boundaries with their own scoped wiki, document set, and department rosters.
- Department-level isolation for HR, Legal, Engineering, etc.
- Global scope for company-wide SOPs, policies, and general knowledge.
- Hard scope enforcement: members only see knowledge from their assigned departments or the global realm - at the API, MCP, and search layers.
π Fine-Grained RBAC
Role-based access control at the department and global levels.
- Built-in roles: Viewer Β· Contributor Β· Editor Β· Admin to control draft, edit, and setting access.
- Granular permissions (
doc:read:own_dept,wiki:edit:all,org:settings:manage, ...). - Audit log for every privileged action - settings changes, plan approvals, and role updates.
π MCP Server for Claude & Other AI Clients
Employees connect Claude Desktop or Claude.ai to Arkon via OAuth 2.1 + PKCE β just add the server URL and sign in through the browser. No manual token copying required. The MCP server exposes:
- Wiki tools -
search_wiki,read_wiki_page,list_wiki_pages,read_wiki_index. - Source drill-down -
get_source,get_source_outline,get_source_pages,list_sources. - Edit workflow -
propose_wiki_edit,edit_wiki_page,list_pending_drafts,review_draft,approve_draft,reject_draft. - Discovery -
list_knowledge_types,get_knowledge_type_docs.
All tools enforce per-token scope (department, knowledge type, source list).
π§° AI Skills Distribution
Upload custom agent packages once and distribute them across the org.
- Versioned skill packages (.zip with
SKILL.md). - Department-scoped visibility.
- Contribution workflow for end-user updates.
π€ Pluggable AI Providers
Catalog-driven selection - admins pick from a curated list with context window, cost, and capability metadata on display.
- LLM: Anthropic Claude (Opus / Sonnet / Haiku 4.x), Google Gemini (3.x Pro / Flash / Flash-Lite, 2.5), OpenAI (GPT-5.x, GPT-4.x).
- Embedding: Google
gemini-embedding-*, OpenAItext-embedding-3-*- switchable with online re-embed migration (active model atomically flipped on completion, no zero-result search window). - Vision: Google Gemini Flash, OpenAI GPT-4o family.
π Privacy & Security First
- Self-hosted. Deploy on-prem or in your private cloud via Docker.
- No telemetry. Outbound traffic goes only to the AI provider you choose.
- Encrypted at rest. API keys stored with Fernet encryption in PostgreSQL.
π οΈ Tech Stack
<p align="center"> <img src="docs/assets/arkon-architecture.png" alt="Arkon Architecture" width="720"> </p>
- Backend: FastAPI Β· PostgreSQL + pgvector Β· Redis (arq workers) Β· MinIO
- Frontend: Next.js Β· Tailwind CSS
- AI integration: Model Context Protocol via FastMCP
- Document parsing: PDF, DOCX, DOC, plain text, URLs, embedded images
π» Server Requirements
Arkon 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:
| Starter | Team | Enterprise | |
|---|---|---|---|
| Team size | 1 β 20 | 20 β 100 | 100+ |
| vCPU | 2 cores | 4 cores | 8+ cores |
| RAM | 4 GB | 8 GB | 16+ GB |
| Storage | 40 GB SSD | 100 GB SSD | 250+ GB NVMe SSD |
| OS | Ubuntu 22.04+ / Debian 12+ | Ubuntu 22.04+ / Debian 12+ | Ubuntu 22.04+ / Debian 12+ |
| Use case | Evaluation / small teams | Departmental deployment | Organization-wide rollout |
[!NOTE]
- RAM is the primary bottleneck β the MRP pipeline workers load large LLM context windows into memory during wiki compilation.
- Storage scales with your document corpus β pgvector indexes, MinIO file storage, and PostgreSQL WAL logs are the main consumers.
- All AI inference happens externally (Anthropic / Google / OpenAI APIs), so GPU is not required.
- A reverse proxy (Nginx / Caddy) with SSL is recommended for production. See Setup Guide.
π¦ Quick Start (Docker)
[!NOTE] Arkon is built for teams, not individuals. If you're looking for a personal knowledge setup, Obsidian + Claude Skills is a much simpler fit.
Not a tech person? Skip the self-hosting hassle β 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.
Prerequisites: Docker & Docker Compose, plus an API key from your preferred AI provider (Anthropic, Google, or OpenAI).
-
Clone the repository:
git clone https://github.com/nduckmink/arkon.git cd arkon -
Configure environment:
cp .env.docker.example .env.docker # Edit .env.docker - set SECRET_KEY, admin credentials, and Postgres/MinIO secrets -
Launch:
docker compose --env-file .env.docker up -d --build -
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.
β See Setup Guide for development mode and the full env reference.
π Connecting Claude
In Claude Desktop or Claude.ai β Settings β Connectors, add a custom connector:
- Name:
Arkon - URL:
https://your-arkon-server/mcp
Click Connect β a browser window opens with the Arkon login form β sign in with your Arkon credentials β done. Arkon uses OAuth 2.1 + PKCE so no manual token setup is required.
To make Claude consistently use Arkon, add this to Claude's Custom Instructions (Settings β Custom Instructions):
Whenever answering questions related to the company β its processes, products,
people, departments, policies, or projects β always search Arkon first using
the search_wiki tool before relying on general knowledge.
For stronger enforcement, create a Project in Claude Desktop, attach Arkon as a connector, and paste the same text as Project Instructions.
<p align="center"> <img src="docs/assets/arkon-in-use-of-claude.png" alt="Arkon in use with Claude Desktop" width="720"> </p>
β See MCP & Claude for the complete tool reference.
πΊοΈ Roadmap
- [x] MRP Pipeline - deterministic compilation with plan review, page merge, and resume-on-crash.
- [x] MCP Server - scoped wiki + source + draft tools.
- [x] Department & Global Scopes - department isolation with RBAC.
- [x] Wiki draft & revision workflow - propose, review, approve, rollback.
- [x] AI Skills - versioned, department-scoped agent packages.
- [x] Catalog-driven model selection - LLM, embedding, and vision picked from a curated list with cost/context-window metadata.
- [x] Online embedding migration - atomic re-embed with no search downtime.
- [x] Audit log - privileged actions tracked.
- [ ] Rich media ingestion - bulk folder upload with images, videos, and Excel/spreadsheet parsing baked into the MRP pipeline.
- [x] Usage analytics dashboard
- [ ] External data import - connectors for SharePoint, Google Drive, Notion, and other common org data sources.
- [ ] Arkon CLI - one-command setup for employees.
- [ ] Notification system - for draft reviews and plan approvals.
β Star History
π License
Arkon is licensed under the PolyForm Internal Use License 1.0.0. Free for internal business operations; you may not offer Arkon as a service to third parties.
For enterprise support or custom integrations, please contact the maintainers.
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.
π¬ Contact
Main Author Minh Nguyen (Nguyα» n Δα»©c Minh) β Vietnam (GMT+7) Β· Fluent English βοΈ duckmink.bitsness@gmail.com
Company BITSNESS TECHNOLOGY AND SOLUTIONS COMPANY LIMITED βοΈ bitsness.ad@bitsness.vn
For enterprise inquiries, demo requests, or custom integrations β email us directly.
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