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 magnusquest/startgg-mcp --skill design-mcp-servergit clone --depth 1 https://github.com/magnusquest/startgg-mcpWrote 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/magnusquest/startgg-mcp/design-mcp-server)<a href="https://agentmods.dev/skills/magnusquest/startgg-mcp/design-mcp-server"><img src="https://agentmods.dev/badge/skills/magnusquest/startgg-mcp/design-mcp-server/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/magnusquest/startgg-mcp/design-mcp-server"><img src="https://agentmods.dev/badge/skills/magnusquest/startgg-mcp/design-mcp-server.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 | $0.00062 | $0.03652 |
| Opus 5 | $0.00031 | $0.01826 |
| Sonnet 5 | $0.00012 | $0.00730 |
| Haiku 4.5 | $0.00006 | $0.00365 |
Grade A, and why
design-mcp-server 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 10d 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 — 338 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to Use
- User says "I want to build a ___ MCP server"
- User has an API, database, or system they want to expose to LLMs
- User wants to plan tools before scaffolding
- Existing server needs a new capability area (design the addition, not just a single tool)
Do NOT use for single-tool additions — use add-tool directly.
Inputs
Gather before designing. Ask the user if not obvious from context:
- Domain — what system, API, or capability is this server wrapping?
- Data sources — APIs, databases, file systems, external services?
- Target users — what will the LLM (and its human) be trying to accomplish?
- Scope constraints — read-only? write access? admin operations? what's off-limits?
If the domain has a public API, read its docs before designing. Don't design from vibes.
Steps
1. Research External Dependencies
Before designing, verify the APIs and services the server will wrap.
If the Agent tool is available, spawn background agents to research in parallel while you proceed with domain mapping:
- Fetch API docs, confirm endpoint availability, auth methods, rate limits
- Check for official SDKs or client libraries (npm packages)
- Note any API quirks, pagination patterns, or data format considerations
If the Agent tool is not available, do this research inline — fetch docs, read SDK readmes, confirm assumptions before committing them to the design.
2. Map the Domain
List the concrete operations the underlying system supports. Group by domain noun.
Example for a project management API:
| Noun | Operations |
|---|---|
| Project | list, get, create, archive |
| Task | list (by project), get, create, update status, assign, comment |
| User | list, get current |
This is the raw material. Not everything becomes a tool.
3. Classify into MCP Primitives
| Primitive | Use when | Examples |
|---|---|---|
| Tool | Needs parameters beyond a simple ID, has side effects, or requires LLM decisions about inputs | Search, create, update, analyze, transform |
| Resource | Addressable by stable URI, read-only, useful as injectable context | Config, schemas, status, entity-by-ID lookups |
| Prompt | Reusable message template that structures how the LLM approaches a task | Analysis framework, report template, review checklist |
| Neither | Internal detail, admin-only, not useful to an LLM | Token refresh, webhook setup, migrations |
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.
- 10d ago First seen · 338 lines · 62 tokens per session scan A 074917cf4c0d
design-mcp-server is a skill published in the GitHub repository magnusquest/startgg-mcp (1 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 62 tokens to every session and 3,652 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 2026-08-31.
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