augments-mcp-server: Comprehensive MCP server providing real-time framework documentation access for Claude Code with intelligent

by augmnt · MCP Server · ★ 127

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install augments-mcp-server

claude mcp add -s user augments -- npx -y @augmnt-sh/augments-mcp-server
git clone https://github.com/augmentscode/augments-mcp-server.git

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 76/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

ai-toolsasynccachingclaude-codedeveloper-toolsframeworkmcpmodel-context-protocolpython

Quick Facts

Stars127
Forks20
LanguageTypeScript
CategoryMCP Server
LicenseMIT
Quality Score76/100
Open Issues1
Last Updated2026-03-13
Created2025-07-20
Platformsclaude-code, mcp, node
Est. Tokens~108k

About augments-mcp-server

A next-generation framework documentation provider for Claude Code via Model Context Protocol (MCP). Returns types + prose + examples with context-aware formatting for any npm package — not just curated ones. mcp-name: dev.augments/mcp What's New in v7 Version 7.0 is the biggest upgrade yet — documentation-first search, 4 new tools, BM25 indexing, and production-grade reliability.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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