No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by dnotitia · MCP Server · ★ 161
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is akb safe to install? View the security audit →
AKB — Agent Knowledge Base Organizational memory for AI agents. Git-backed knowledge base served over the Model Context Protocol (MCP) — agents read and write directly with hybrid semantic + keyword search, structured tables, files, and a URI graph. Drop-in alternative to Confluence / Notion for Claude Code, Cursor, Windsurf, and any MCP-aware agent. Works with Any agent client that speaks MCP (Streamable HTTP or stdio): Claude Code — CLI / VS Code / JetBrains Claude Desktop — macOS / Windows Cursor, Windsurf, Cline, Continue — via the stdio proxy Custom agents — direct HTTP with a Bearer token Plugins Beyond raw MCP access, AKB ships ready-made agent plugins for Claude Code and Codex that wrap common vault workflows: akb-wiki — ingest a source (local file, web URL, GitHub PR / release / commit, Confluence page, o
| Stars | 161 |
| Forks | 10 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 62.2457052871641/100 |
| Open Issues | 8 |
| Last Updated | 2026-10-01 |
| Created | 2026-05-07 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~18k |
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akb is AKB — Agent Knowledgebase. Organizational memory for AI agents: vault-scoped docs / tables / files unified by URI graph, served over MCP.. It is categorized as a MCP Server with 161 GitHub stars.
akb is primarily written in Python. It covers topics such as agent, claude, claude-code.
You can find installation instructions and usage details in the akb GitHub repository at github.com/dnotitia/akb. The project has 161 stars and 10 forks, indicating an active community.
The top alternatives to akb on Agent Skills Hub include octocode, shodh-memory, orchestkit. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: