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 jpantsjoha/ai-native-developer-experience --skill mcp-server-scaffoldgit clone --depth 1 https://github.com/jpantsjoha/ai-native-developer-experienceWrote 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/jpantsjoha/ai-native-developer-experience/mcp-server-scaffold)<a href="https://agentmods.dev/skills/jpantsjoha/ai-native-developer-experience/mcp-server-scaffold"><img src="https://agentmods.dev/badge/skills/jpantsjoha/ai-native-developer-experience/mcp-server-scaffold.svg" alt="Measured on agentmods" 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 | $0.00053 | $0.00794 |
| Opus 5 | $0.00026 | $0.00397 |
| Sonnet 5 | $0.00011 | $0.00159 |
| Haiku 4.5 | $0.00005 | $0.00079 |
Grade A, and why
mcp-server-scaffold 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 8d 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MCP Server Scaffold
Agents call tools. Tools call infrastructure. This boundary is the governance seam. Do not collapse it.
An MCP server is a contract between an agent and the capabilities it is allowed to use. Its value is not in what it exposes — it is in what it deliberately withholds.
When to use
- Adding a new MCP server to an agent system
- Reviewing an existing MCP server for scope creep or security gaps
- Deciding which capabilities to expose to an agent (and which to explicitly deny)
- Governing an agent that has been given "too much access"
Procedure
-
Define the tool seam — before writing any server code, list:
- What capabilities does the agent legitimately need?
- What capabilities does the underlying system have that the agent must NOT access?
- What is the minimum viable tool surface?
-
Author the tool manifest — for each tool:
Tool: <name> Description: <one sentence — what it does and when to call it> Input schema: <typed fields with constraints> Output schema: <typed fields> Side effects: <what it changes in the world — none / read-only / write / external-call> Auth required: <yes/no and mechanism> Rate limit: <calls/minute or none> -
Enforce least-privilege at the server — the MCP server holds the credentials and enforces the scope. The agent receives only the tool interface. Key rules:
- Read tools and write tools are separate, explicitly named operations.
- No tool exposes raw SQL, raw shell execution, or raw filesystem access.
- No tool accepts arbitrary code or query strings from the agent without validation.
-
Add input validation at the boundary — every tool validates its inputs before executing. Reject malformed inputs with a structured error, not an exception trace.
-
Log every tool invocation — at minimum: tool name, caller identity, input summary (no secrets), output summary, timestamp, and latency. These logs are your audit trail.
-
Test the refusal surface — confirm that:
- A call to a non-existent tool returns a clean error, not a server crash.
- An out-of-scope request (e.g. an agent trying to read data it is not authorised for) is rejected with a clear error.
- Invalid inputs are rejected before any side effect occurs.
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.
- 8d ago First seen · 68 lines · 53 tokens per session scan A 3fbfb9ab7c18
mcp-server-scaffold is a skill published in the GitHub repository jpantsjoha/ai-native-developer-experience (11 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 53 tokens to every session and 794 once invoked, about $0.0003 per session on Opus 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 2026-08-30.
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