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 monkey1wizard/Golem-Agents-Legion --skill mcp-buildergit clone --depth 1 https://github.com/monkey1wizard/Golem-Agents-LegionWrote 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/monkey1wizard/golem-agents-legion/mcp-builder)<a href="https://agentmods.dev/skills/monkey1wizard/golem-agents-legion/mcp-builder"><img src="https://agentmods.dev/badge/skills/monkey1wizard/golem-agents-legion/mcp-builder.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 | $0.00061 | $0.02168 |
| Opus 5 | $0.00030 | $0.01084 |
| Sonnet 5 | $0.00012 | $0.00434 |
| Haiku 4.5 | $0.00006 | $0.00217 |
Grade A, and why
mcp-builder 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 2d 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.
This is a copy
83% identical to mcp-builder — 21 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 252 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MCP Server Development Guide
Overview
Create MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks.
When current documentation is needed, prefer MCP tools over generic recollection:
- Use
context7for library, framework, SDK, and package documentation - Use
fetchfor raw MCP spec pages, GitHub READMEs, and general web documentation
When evaluating an MCP server, use Playwright MCP only when the server exposes browser-visible behavior such as a Web UI, rendered docs, or end-user browser flows that cannot be verified well through Inspector or CLI-only checks. API-only or read-only server evaluation should stay on MCP Inspector, unit tests, and deterministic CLI paths.
If these MCPs are unavailable, fall back to direct web retrieval.
Process
🚀 High-Level Workflow
Creating a high-quality MCP server involves four main phases:
Phase 1: Deep Research and Planning
1.1 Understand Modern MCP Design
API Coverage vs. Workflow Tools: Balance comprehensive API endpoint coverage with specialized workflow tools. Workflow tools can be more convenient for specific tasks, while comprehensive coverage gives agents flexibility to compose operations. Performance varies by client—some clients benefit from code execution that combines basic tools, while others work better with higher-level workflows. When uncertain, prioritize comprehensive API coverage.
Tool Naming and Discoverability:
Clear, descriptive tool names help agents find the right tools quickly. Use consistent prefixes (e.g., github_create_issue, github_list_repos) and action-oriented naming.
Context Management: Agents benefit from concise tool descriptions and the ability to filter/paginate results. Design tools that return focused, relevant data. Some clients support code execution which can help agents filter and process data efficiently.
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- LICENSE.txt 11 KB
- reference/evaluation.md 21 KB
- reference/mcp_best_practices.md 7.1 KB
- reference/node_mcp_server.md 28 KB
- reference/python_mcp_server.md 25 KB
- scripts/connections.py 4.8 KB runs code
- scripts/evaluation.py 12 KB runs code
- scripts/example_evaluation.xml 1.2 KB
- scripts/requirements.txt 29 B
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.
- 2d ago First seen · 252 lines · 61 tokens per session scan A 40404368e5ea
mcp-builder is a skill published in the GitHub repository monkey1wizard/Golem-Agents-Legion (15 stars, last pushed 4d ago), licensed MIT. It adds 61 tokens to every session and 2,168 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 83% identical to mcp-builder, differing in 21 lines, and is treated as a copy.
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