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.
npx skills add fabioc-aloha/Alex_Skill_Mall --skill mcp-server-buildgit clone --depth 1 https://github.com/fabioc-aloha/Alex_Skill_MallWrote 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/skills/fabioc-aloha/alex_skill_mall/mcp-server-build)<a href="https://agentmods.dev/skills/fabioc-aloha/alex_skill_mall/mcp-server-build"><img src="https://agentmods.dev/badge/skills/fabioc-aloha/alex_skill_mall/mcp-server-build/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/skills/fabioc-aloha/alex_skill_mall/mcp-server-build"><img src="https://agentmods.dev/badge/skills/fabioc-aloha/alex_skill_mall/mcp-server-build.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00041 | $0.01424 |
| Opus 5.5 | $0.00016 | $0.00570 |
| Sonnet 5.5 | $0.00008 | $0.00285 |
| Haiku 4.5 | $0.00004 | $0.00142 |
Grade A, and why
mcp-server-build 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.
How it starts
The opening of the file, as written. The whole thing — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Build an MCP Server
Samples below are minimal but complete: each one runs.
TypeScript
npm install @modelcontextprotocol/sdk zod
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";
const server = new McpServer({ name: "my-mcp-server", version: "1.0.0" });
server.tool(
"list_items",
"List items with pagination. Use before acting on a specific item.",
{ page: z.number().default(1), limit: z.number().max(100).default(20) },
async ({ page, limit }) => {
try {
const items = await api.listItems({ page, limit });
return {
content: [{
type: "text",
text: JSON.stringify({ items, page, hasMore: items.length === limit }),
}],
};
} catch (error) {
return {
content: [{
type: "text",
text: `Error: ${error.message}. Try: check API key, verify endpoint, reduce page size.`,
}],
isError: true,
};
}
},
);
await server.connect(new StdioServerTransport());
Python
pip install mcp
from mcp.server.fastmcp import FastMCP
from pydantic import BaseModel, Field
mcp = FastMCP("my-mcp-server")
class ListParams(BaseModel):
page: int = Field(default=1, description="1-based page number")
limit: int = Field(default=20, le=100, description="Items per page, max 100")
@mcp.tool(description="List items with pagination. Use before acting on one.")
async def list_items(params: ListParams) -> dict:
items = await api.list_items(page=params.page, limit=params.limit)
return {"items": items, "page": params.page, "hasMore": len(items) == params.limit}
if __name__ == "__main__":
mcp.run()
FastMCP turns the Pydantic model into the input schema, so field descriptions and constraints reach the agent. Put the constraint in the model rather than validating by hand in the body.
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 · 199 lines · 41 tokens per session scan A fbb32389f262
mcp-server-build is a skill published in the GitHub repository fabioc-aloha/Alex_Skill_Mall (5 stars, last pushed yesterday), licensed MIT. It adds 41 tokens to every session and 1,424 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-14.
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Use when a manager wants to proactively retain top-performing direct reports — because high performers have the most options to leave and require active, differentiated management attention to stay engaged and challenged.
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