by ismailperim · MCP Server · ★ 31
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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. Full audit →
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.
| Stars | 31 |
| Forks | 0 |
| Language | Go |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 65/100 |
| Open Issues | 4 |
| Last Updated | 2026-10-12 |
| Created | 2026-09-20 |
| Platforms | claude-code, go, mcp |
| Est. Tokens | ~20k |
Your agents, briefed. Not flooded. Self-hosted context compiler: git-backed team knowledge served to coding agents as token-budgeted bundles over MCP.
These tools work well together with briefd for enhanced workflows:
Looking for a briefd alternative? If you're comparing briefd with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Local-first AI knowledge layer. Extract architecture, query from any AI tool via MCP. Private by architecture.
Turn feature specs into merged PRs with a self-supervising swarm of coding agents — parallel execution, isolat
The hivemind for AI coding agents — persistent team context recorded once and recalled across agents, machines
Comprehensive MCP server providing real-time framework documentation access for Claude Code with intelligent c
Local AI-powered document search and editing with first-in-class hybrid retrieval, LLM answers, WebUI, REST AP
Self-hosted mem0 MCP server for Claude Code. Run a complete memory server against self-hosted Qdrant + Neo4j +
Explore other popular mcp server tools:
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: