Toucan: Official repo of Toucan: Synthesizing 1.5M Tool-Agentic Data from Real-World MCP Environments

by TheAgentArk · MCP Server · ★ 268

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

Security audit verdict: SAFE · quality 56/100

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

Stars268
Forks19
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score56/100
Open Issues4
Last Updated2025-12-16
Created2025-09-30
Platformsmcp, python
Est. Tokens~1625k

About Toucan

🦤 Toucan-1.5M: Toucan-1.5M is the largest fully synthetic tool-agent dataset to date, designed to advance tool use in agentic LLMs. It comprises over 1.5 million trajectories synthesized from 495 real-world Model Context Protocols (MCPs) spanning 2,000+ tools.

Compatible Skills

These tools work well together with Toucan for enhanced workflows:

  • mint-bench — semantic(0.31)+complementary+same_lang+similar_pop+shared_platform (56%)
  • LLM-MM-Agent — semantic(0.30)+complementary+same_lang+similar_pop+shared_platform (56%)
  • AutoTools — semantic(0.26)+complementary+same_lang+similar_pop+shared_platform (54%)
  • code-act — semantic(0.25)+complementary+same_lang+similar_pop+shared_platform (54%)
  • empower-functions — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (52%)

More MCP Server Tools

Explore other popular mcp server tools:

View all MCP Server tools →

Popular Python Agent Tools

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:

View on GitHub → Browse MCP Server tools