mcp-dev-latam: Open-source MCP servers for Latin American commerce — Pix, NF-e, banking, fiscal, logistics, and messaging

Security audit verdict: SAFE · quality 69/100

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

About mcp-dev-latam

MCP Dev LATAM 🌎 Every commerce API your AI agent needs to run a business in Latin America. Brazil 🇧🇷 · Mexico 🇲🇽 · Argentina 🇦🇷 · Colombia 🇨🇴 · Chile 🇨🇱 · Peru 🇵🇪 · plus 4 agentic payment protocols.

Compatible Skills

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

• medusa-agent-skills — semantic(0.37)+complementary+rare_topics+similar_pop+shared_platform (57%)
• shopify-hydrogen-skills — semantic(0.17)+complementary+rare_topics+similar_pop+shared_platform (50%)
• getnote-mcp — semantic(0.31)+same_lang+similar_pop+shared_platform (46%)
• get-physics-done — semantic(0.16)+complementary+similar_pop+shared_platform (46%)

mcp-dev-latam alternative? Top 6 similar tools

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• mcp-fiscal-brasil by DeHor-Labs · ⭐ 335

  Servidor MCP fiscal brasileiro: CNPJ, NF-e, NFS-e, CT-e, SPED, eSocial, Simples Nacional, Reforma 2026. 44 too

• model-context-protocol-resources by cyanheads · ⭐ 293

  Technical overview of the Model Context Protocol, current to the 2026-07-28 spec.

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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:

• SlowMist agent-security taxonomy
• Liu et al., An Empirical Study of Agent Skill Security (2026)
• Our census dataset (DOI 10.5281/zenodo.21292799) · Hugging Face mirror
• How we grade: all 42 rules, the source tiers and known limits
• Full methodology & who runs this