Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/analyticalmonk/fal-ai-skillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/mcp/analyticalmonk/fal-ai-skill/fal)<a href="https://agentmods.dev/mcp/analyticalmonk/fal-ai-skill/fal"><img src="https://agentmods.dev/badge/mcp/analyticalmonk/fal-ai-skill/fal/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/mcp/analyticalmonk/fal-ai-skill/fal"><img src="https://agentmods.dev/badge/mcp/analyticalmonk/fal-ai-skill/fal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
fal scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
{
"fal": {
"type": "http",
"url": "https://docs.fal.ai/mcp"
}
}What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 6 lines scan A df2c886b9005
fal is an MCP server published in the GitHub repository analyticalmonk/fal-ai-skill (8 stars, last pushed 6mo ago), licensed MIT. Its token cost is not measured: an MCP server costs its tool schemas, not its config file. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other mcp servers, from other repositories
roast-my-design-system
Audit your Design System and serve your Agent the rules that keep AI-written UI on-system. Runs locally from the roast-my-design-system npm package.
fal
MCP server "fal", hosted remotely at mcp.fal.ai, as configured in mertagralii/fal.ai-butler.
cadence
MCP server "cadence" as configured in ecliptic-ai/skills. Runs ${CLAUDE_PLUGIN_ROOT}/server/dist/index.js with node. Needs 4 environment variables to run.
playwright
Lets the agent drive a real browser: open pages, click, type, take screenshots and read the accessibility tree, using Playwright. Runs locally from the @playwright/mcp npm package.
context7
Gives the agent up-to-date documentation and code examples for libraries and frameworks, fetched on demand so answers are not stuck at the model's training cutoff. Runs locally from the @upstash/context7-mcp npm package.
docs-langchain
MCP server "docs-langchain", hosted remotely at docs.langchain.com, as configured in langchain-ai/langchain.