Skillzwave Logo
Skillzwave

mcp-builder

17.3
A

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Also in: javascript

Third-Party Agent Skill: Review the code before installing. Agent skills execute in your AI assistant's environment and can access your files. Learn more about security

Installation for Agentic Skill

View all platforms →
skilz install mjunaidca/mjs-agent-skills/mcp-builder
skilz install mjunaidca/mjs-agent-skills/mcp-builder --agent opencode
skilz install mjunaidca/mjs-agent-skills/mcp-builder --agent codex
skilz install mjunaidca/mjs-agent-skills/mcp-builder --agent gemini

First time? Install Skilz: pip install skilz

Works with 22+ AI coding agents

Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...

View All Agents
Download Agent Skill ZIP

Extract and copy to ~/.claude/skills/ then restart Claude Desktop

1. Clone the repository:
git clone https://github.com/mjunaidca/mjs-agent-skills
2. Copy the agent skill directory:
cp -r mjs-agent-skills/docs/taskflow-vault/skills/engineering/mcp-builder ~/.claude/skills/

Need detailed installation help? Check our platform-specific guides:

Related Agentic Skills

claude-permissions

by SpillwaveSolutions

Proactive Claude Code permission manager. Configures permissions via natural language for CLI tools (git, gcloud, aws, kubectl, maven, gradle, npm, do...

100
TECHpython
+javascript+docker

developing-llamaindex-systems

by SpillwaveSolutions

Production-grade agentic system development with LlamaIndex in Python. Covers semantic ingestion (SemanticSplitterNodeParser, CodeSplitter, IngestionP...

99
A
TECHpython
#references#semantic chunking#semantic
+database+github

mastering-langgraph

by SpillwaveSolutions

Build stateful AI agents and agentic workflows with LangGraph in Python. Covers tool-using agents with LLM-tool loops, branching workflows, conversati...

95
A
TECHpython
#references#agents#langgraph
+monitoring

mastering-langgraph

by SpillwaveSolutions

Build stateful AI agents and agentic workflows with LangGraph in Python. Covers tool-using agents with LLM-tool loops, branching workflows, conversati...

95
A
TECHpython
#references#agents#langgraph
+monitoring

Agentic Skill Details

Type
Technical
Meta-Domain
development
Primary Domain
python
Market Score
17.3

Agent Skill Grade

A
Score: 90/100 Click to see breakdown

Score Breakdown

Spec Compliance
13/15
PDA Architecture
27/30
Ease of Use
23/25
Writing Style
9/10
Utility
18/20

Areas to Improve

  • SKILL.md (314 lines) and reference files (719, 970, 602 lines) lack table of contents for navigation
  • Occasional use of 'you must' and 'your implementation' instead of imperative/infinitive
  • Docker/containerization details are in SKILL.md instead of being a separate reference file

Recommendations

  • Add trigger phrases to description for discoverability
  • Add table of contents for files over 100 lines

Graded: 1/24/2026

Developer Feedback

I've been diving into MCP implementations lately, and your approach to wrapping the builder pattern is pretty thoughtful—especially how you handle the validation flow without over-engineering it. Scored a solid 90, so curious what you'd prioritize if you were to iterate on it next.

Links:

The TL;DR

You're at 90/100, A territory. This is based on Anthropic's Claude Skills Best Practices. Your strongest area is Ease of Use (23/25)—the trigger terms and workflow clarity are solid. The weakest spot is Spec Compliance (13/15), mainly because you're only using 1-2 trigger phrases when you could be more explicit.

What's Working Well

  • Layered structure is chef's kiss. SKILL.md stays tight at 314 lines with 5 focused reference files. That's how you do Progressive Disclosure right—no token waste, but comprehensive when developers dig deeper.
  • Your trigger terms nail discoverability. "MCP server," "FastMCP," "Python SDK," "Node SDK"—these activate naturally when someone needs to build something. That's why Ease of Use scored 23/25.
  • The 4-phase workflow is clear. Research → Implementation → Testing → Evaluation, each with actionable subsections and checklists. Developers know exactly what phase they're in and what to do next.
  • Examples in both Python and TypeScript. Shows you understand your audience isn't monolithic. That adds real utility (18/20 there).

The Big One: Missing Navigation in Long Files

Your reference files are dense—719, 970, 602 lines in some cases—but no table of contents. This kills navigation signals and costs you 2-3 points on Progressive Disclosure.

The fix: Add a TOC right after the frontmatter in SKILL.md and any reference file over 100 lines:

## Contents

- [Phase 1: Research](#phase-1-research)
- [Phase 2: Implementation](#phase-2-implementation)
- [Phase 3: Testing](#phase-3-testing)
- [Phase 4: Evaluation](#phase-4-evaluation)

This takes 10 minutes and gets you to 93/100 territory.

Other Things Worth Fixing

  1. Docker section overstay. You've got 65 lines of Docker/containerization details embedded in SKILL.md (lines 240-304). Move this to reference/docker_deployment.md and link it. Keeps the main file tighter and follows your own layering pattern.

  2. Second-person voice creeping in. Phrases like "you must start the MCP server" and "your implementation" should be imperative: "Start the MCP server separately" or "Configure the implementation." Small shift, but Writing Style moves from 9/10 to 10/10.

  3. Add more trigger phrases to the frontmatter description. You've got good ones, but "MCP transport mechanisms," "tool definition," and "resource registration" would help the skill surface in more searches.

Quick Wins

  • Add TOC to files >100 lines (+2 points)
  • Move Docker content to separate reference file (+1 point)
  • Shift second-person to imperative voice (+1 point)
  • Expand trigger phrases in description metadata (+1 point)

That's potentially 95/100 with minimal effort. You're already at A-grade—these are just refinements.


Checkout your skill here: SkillzWave.ai | SpillWave We have an agentic skill installer that install skills in 14+ coding agent platforms. Check out this guide on how to improve your agentic skills.

Report Security Issue

Found a security vulnerability in this agent skill?