innovation-lab-examples: 80+ production-ready AI agent examples in Python — build autonomous agents, multi-agent systems and agentic AI

by fetchai · MCP Server · ★ 1.2k

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

How to install innovation-lab-examples

git clone https://github.com/fetchai/innovation-lab-examples.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 67/100

None of the 43 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 43 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.

a2a-protocolagentic-aiagentverseai-agentai-agent-examplesai-agent-frameworkai-agentsasi-oneautonomous-agentscrewai

Quick Facts

Stars1,171
Forks85
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score67/100
Open Issues8
Last Updated2026-09-01
Created2025-06-16
Platformsclaude-code, gemini, mcp, python
Est. Tokens~18k

About innovation-lab-examples

Fetch.ai Innovation Lab Examples 80+ production-ready AI agent examples in Python Build autonomous AI agents, multi-agent systems and agentic AI workflows with uAgents, ASI:One, Agentverse, MCP, the A2A protocol, LangChain, CrewAI, Gemini, Claude and OpenAI.

Compatible Skills

These tools work well together with innovation-lab-examples for enhanced workflows:

  • agentops — semantic(0.22)+complementary+shared_fw(crewai,langchain,openai)+same_lang+similar_pop+shared_platform (78%)
  • Agentic-AI-Systems — semantic(0.21)+complementary+shared_fw(crewai,langchain,openai)+same_lang+similar_pop+shared_platform (78%)
  • autonomous-hr-chatbot — semantic(0.32)+complementary+shared_fw(langchain,openai)+same_lang+similar_pop+shared_platform (77%)
  • loopgain — semantic(0.19)+complementary+shared_fw(crewai,langchain,openai)+same_lang+similar_pop+shared_platform (77%)
  • Tiger — semantic(0.23)+complementary+shared_fw(crewai,langchain)+same_lang+similar_pop+shared_platform (74%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 43 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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