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 DAWNCR0W · MCP Server · ★ 289
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is affine-mcp-server safe to install? View the security audit →
AFFiNE MCP Server A Model Context Protocol (MCP) server for AFFiNE. It exposes AFFiNE workspaces and documents to AI assistants over stdio (default) or HTTP () and supports both AFFiNE Cloud and self-hosted deployments. Table of Contents Overview Choose Your Path Quick Start Compatibility Matrix Tool Surface Documentation Map Verify Your Setup Security and Scope Development Release Notes License Support Overview AFFiNE MCP Server is designed for three common scenarios: Run a local stdio MCP server for Claude Code, Codex CLI, Cursor, or Claude Desk
| Stars | 289 |
| Forks | 72 |
| Language | JavaScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 75.8057613102054/100 |
| Last Updated | 2026-09-22 |
| Created | 2025-08-11 |
| Platforms | claude-code, codex, mcp, node |
| Est. Tokens | ~15k |
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affine-mcp-server is Model Context Protocol server for AFFiNE. Connect AI assistants to AFFiNE workspaces, documents, databases, and collaboration APIs over stdio or HTTP.. It is categorized as a MCP Server with 289 GitHub stars.
affine-mcp-server is primarily written in JavaScript. It covers topics such as affine, ai-assistants, claude.
You can find installation instructions and usage details in the affine-mcp-server GitHub repository at github.com/DAWNCR0W/affine-mcp-server. The project has 289 stars and 72 forks, indicating an active community.
affine-mcp-server is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to affine-mcp-server on Agent Skills Hub include apple-docs-mcp, OpenContext, atlassian-mcp-server. 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: