ultra-mcp: 100x Your Claude Code, Gemini CLI, Cursor and/or any coding tools with MCP client support

by RealMikeChong · MCP Server · ★ 275

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

How to install ultra-mcp

npm install -g ultra-mcp
npx -y ultra-mcp config

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 74/100

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.

Quick Facts

Stars275
Forks19
LanguageTypeScript
CategoryMCP Server
LicenseMIT
Quality Score74/100
Open Issues3
Last Updated2025-08-25
Created2025-06-28
Platformsclaude-code, cli, gemini, mcp, node
Est. Tokens~64k

About ultra-mcp

Ultra MCP All Models. One Interface. Zero Friction. 🚀 Ultra MCP - A Model Context Protocol server that exposes OpenAI, Gemini, Azure OpenAI, and xAI Grok AI models through a single MCP interface for use with Claude Code and Cursor. Stop wasting time having meetings with human. Now it's time to ask AI models do this.

Compatible Skills

These tools work well together with ultra-mcp for enhanced workflows:

  • ccmanager — semantic(0.31)+complementary+same_lang+similar_pop+shared_platform (56%)
  • prompt-line — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (53%)
  • vibekit — semantic(0.23)+complementary+same_lang+similar_pop+shared_platform (53%)
  • agent-rules — semantic(0.23)+complementary+same_lang+similar_pop+shared_platform (53%)
  • browser-echo — semantic(0.21)+complementary+same_lang+similar_pop+shared_platform (52%)

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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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