volcano-agent-sdk: Build AI agents that seamlessly combine LLM reasoning with real-world actions via MCP tools

by Kong · MCP Server · ★ 406

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

Security audit verdict: SAFE · quality 71/100

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.

agenticagentic-aiagentic-frameworkagentsaiartificial-intelligenceautomationgenaimcpmcp-client

Quick Facts

Stars406
Forks32
LanguageTypeScript
CategoryMCP Server
Quality Score71/100
Open Issues10
Last Updated2026-02-12
Created2025-09-22
Platformscli, mcp, node
Est. Tokens~689k

About volcano-agent-sdk

🌋 Volcano Agent SDK The TypeScript SDK for Multi-Provider AI Agents Build agents that chain LLM reasoning with MCP tools. Mix OpenAI, Claude, Mistral in one workflow. Parallel execution, branching, loops. Native retries, streaming, and typed errors.

Compatible Skills

These tools work well together with volcano-agent-sdk for enhanced workflows:

  • ClawRecipes — semantic(0.20)+complementary+rare_topics+same_lang+similar_pop+shared_platform (56%)
  • agentic — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (51%)
  • agent-rules — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (51%)
  • claude-code-tamagotchi — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (50%)
  • sim — semantic(0.19)+complementary+same_lang+shared_platform (47%)

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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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