by andrefetch · MCP Server · ★ 191
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
pip install postalcli
Taken from the project's README on GitHub.
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.
| Stars | 191 |
| Forks | 33 |
| Language | Python |
| Category | MCP Server |
| License | GPL-3.0 |
| Quality Score | 65/100 |
| Last Updated | 2026-11-06 |
| Created | 2026-06-26 |
| Platforms | cli, mcp, python |
| Est. Tokens | ~16k |
Postal An open-source AI coding agent that lives in your terminal. Plans, edits, runs, and reviews code with any model on OpenRouter. Postal connects to LLMs through OpenRouter, reads and edits your code with a built-in tool set, runs shell commands, delegates to specialized sub-agents, and streams everything through a full-screen TUI.
These tools work well together with postal for enhanced workflows:
Looking for a postal alternative? If you're comparing postal 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.
Open source AI coding platform with Web IDE, multi-agent system, 37+ tools, MCP protocol. MIT licensed.
Agent samples built using the Strands Agents SDK.
Official python implementation of UTCP. UTCP is an open standard that lets AI agents call any API directly, wi
Penpot MCP server
All-in-one MCP server that can connect your AI agents to any native endpoint, powered by UTCP
MCP Server for Facebook ADs Library - Get instant answers from FB's ad library
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: