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 FarhanAliRaza · MCP Server · ★ 237
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is claude-context-local safe to install? View the security audit →
Claude Context without the cloud. Semantic code search that runs 100% locally using EmbeddingGemma. No API keys, no costs, your code never leaves your machine. 🔍 Find code by meaning, not strings 🔒 100% local - completely private 💰 Zero API costs - forever free ⚡ Fewer tokens in Claude Code and fast local
| Stars | 237 |
| Forks | 30 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 76.3164222576764/100 |
| Open Issues | 11 |
| Last Updated | 2025-11-13 |
| Created | 2025-09-06 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~10k |
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claude-context-local is Code search MCP for Claude Code. Make entire codebase the context for any coding agent. Embeddings are created and stored locally. No API cost.. It is categorized as a MCP Server with 237 GitHub stars.
claude-context-local is primarily written in Python. It covers topics such as agent, ai-coding, claude.
You can find installation instructions and usage details in the claude-context-local GitHub repository at github.com/FarhanAliRaza/claude-context-local. The project has 237 stars and 30 forks, indicating an active community.
The top alternatives to claude-context-local on Agent Skills Hub include Mysti, arcade-mcp, agentsys. 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: