Atlas / Skills / jezweb / Mcp Builder

Mcp BuilderSAFE

skills/jezweb/mcp-builder

Skills for Claude Code CLI such as full stack dev Cloudflare, React, Tailwind v4, and AI integrations.

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
—
Hosts
2 documented
License
MIT
Stars
1,059
01

Overview

Skills for Claude Code CLI such as full stack dev Cloudflare, React, Tailwind v4, and AI integrations.

Read from source at commit be410003e718OBSERVED · 2026-10-12
02

Install

Commands as the repository documents them. They are shown, not run.

pip install fastmcp
03

Host compatibility

What the documentation claims. We have not run a compatibility test.

HostStatusNotes
claude-codementioned
claude-desktopmentioned
04

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: mcp-builder
description: "Build MCP servers in Python with FastMCP. Define tools / resources / prompts, build the server, test locally, deploy to FastMCP Cloud or Docker. Use whenever the user mentions building an MCP server, exposing tools to LLMs, FastMCP, building a Claude integration, or troubleshooting FastMCP module-level server, storage, lifespan, middleware, OAuth, or deployment errors."
compatibility: claude-code-only
---

# MCP Builder

Build a working MCP server from a description of the tools you need. Produces a deployable Python server using FastMCP.

## Workflow

### Step 1: Define What to Expose

Ask what the server needs to provide:

- **Tools** -- Functions Claude can call (API wrappers, calculations, file operations)
- **Resources** -- Data Claude can read (database records, config, documents)
- **Prompts** -- Reusable prompt templates with parameters

A brief like "MCP server for querying our customer database" is enough.

### Step 2: Scaffold the Server

```bash
pip install fastmcp
```

Create the server file. The server instance MUST be at module level:

```python
from fastmcp import FastMCP

# MUST be at module level for FastMCP Cloud
mcp = FastMCP("My Server")

@mcp.tool()
async def search_customers(query: str) -> str:
    """Search customers by name or email."""
    # Implementation here
    return f"Found customers matching: {query}"

@mcp.resource("customers://{customer_id}")
async def get_customer(customer_id: str) -> str:
    """Get customer details by ID."""
    return f"Customer {customer_id} details"

if __name__ == "__main__":
    mcp.run()
```

### Step 3: Add Companion CLI Scripts (Optional)

For Claude Code terminal use, add scripts alongside the MCP server:

```
my-mcp-server/
├── src/index.ts          # MCP server (for Claude.ai)
├── scripts/
│   ├── search.ts         # CLI version of search tool
│   └── _shared.ts        # Shared auth/config
├── SCRIPTS.md            # Documents available scripts
└── package.json
```

CLI scripts provide file I/O, batch processing, and richer output that MCP can't.
See `assets/SCRIPTS-TEMPLATE.md` and `assets/script-template.ts` for TypeScript templates.

### Step 4: Test Locally

**Quick test -- run directly:**

```bash
python server.py
```

**Dev mode with inspector UI (recommended):**

```bash
fastmcp dev server.py
# Opens inspector at http://localhost:5173
# Hot reload, detailed logging, tool/resource inspection
```

**HTTP mode for remote clients:**

```bash
python server.py --transport http --port 8000
```

**Automated test script using FastMCP Client:**

```python
import asyncio
from fastmcp import Client

async def test_server(server_path):
    async with Client(server_path) as client:
        # List everything
        tools = await client.list_tools()
        resources = await client.list_resources()
        prompts = await client.list_prompts()

        print(f"Tools: {[t.name for t in tools]}")
        print(f"Resources: {[r.uri for r in resources]}")
        print(f"Prompts: {[p.name for p in prompts]}")

        # Call first tool
        if tools:
            result = await client.call_tool(tools[0].name, {})
            print(f"Tool result: {result}")

        # Read first resource
        if resources:
            data = await client.read_resource(resources[0].uri)
            print(f"Resource data: {data}")

asyncio.run(test_server("server.py"))
```

### Step 5: Pre-Deploy Checklist

Run these checks before deploying. All required checks must pass.

**Required (will cause deploy failure):**

1. Server file exists
2. Python syntax valid: `python3 -m py_compile server.py`
3. Module-level server object (not inside a function):
   ```bash
   grep -q "^mcp = FastMCP\|^server = FastMCP\|^app = FastMCP" server.py
   ```
4. `requirements.txt` exists with PyPI packages only (no `git+`, `-e`, `.whl`, `.tar.gz`)
5. No hardcoded secrets (check for `api_key = "..."` patterns excluding `os.getenv`/`os.environ`)

**Advisory (warnings):**

6. `fastmcp` listed in requirements.txt
7. `.gitignore` includes `.env`
8. No circular imports
9. Git repository initialised with remote
10. Server can load: `timeout 5 fastmcp inspect server.py`

### Step 6: Deploy

**FastMCP Cloud (simplest):**

```bash
git add . && git commit -m "Ready for deployment"
git push -u origin main
# Visit https://fastmcp.cloud, connect repo, add env vars, deploy
# URL: https://your-project.fastmcp.app/mcp
```

Cloud requirements:
- Module-level server object named `mcp`, `server`, or `app`
- PyPI dependencies only in `requirements.txt`
- Public GitHub repository
- Environment variables for secrets (no hardcoded values)
- Auto-deploys on push to main, PR preview deployments

**Docker (self-hosted):**

```dockerfile
FROM python:3.12-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
EXPOSE 8000
CMD ["python", "server.py", "--transport", "http", "--port", "8000"]
```

**Cloudflare Workers (edge):**
Build it in TypeScript with Cloudflare's `agents` SDK (`McpAgent`); Cloudflare's remote MCP server docs carry the current template.

---

## Critical Patterns

### Module-Level Server Instance

FastMCP Cloud requires the server instance at module level:

```python
# CORRECT
mcp = FastMCP("My Server")

@mcp.tool()
def my_tool(): ...

# WRONG -- Cloud can't find the server
def create_server():
    mcp = FastMCP("My Server")
    return mcp

# FIX for factory pattern -- export at module level
def create_server() -> FastMCP:
    mcp = FastMCP("server")
    return mcp
mcp = create_server()
```

### Type Annotations Required

FastMCP uses type annotations to generate tool schemas:

```python
@mcp.tool()
async def search(
    query: str,           # Required parameter
    limit: int = 10,      # Optional with default
    tags: list[str] = []  # Complex types supported
) -> str:
    """Docstring becomes the tool description."""
    ...
```

### Error Handling

Return errors as strings, don't raise exceptions:

```python
@m
05

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codePASS
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
declared (5 observation(s))
Shell
none-observed
Dependencies
not all pinned
Secrets in source
none-found

Findings (1)

LOWSupply chain · supply.unpinned · CWE-829, CWE-1357
assets/requirements.txt
fastmcp, py-key-value-aio, cryptography, httpx, python-dotenv, pydantic, psutil, asyncio-extras
Why it matters. 8 requirement(s) not pinned with ==
Fix. pin exact versions

Gates applied: no_behavioural_pass.

Audited 2026-10-12 · audit v0.4.1 · source sha be410003e718full audit observations/trust-audit/skill/jezweb__mcp-builder.json · Report an issue / request a re-scan
06

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-12be410003e718SAFEB89first audit
07

Questions

What does the Mcp Builder skill do?

Skills for Claude Code CLI such as full stack dev Cloudflare, React, Tailwind v4, and AI integrations.

Is Mcp Builder safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Mcp Builder access on my machine?

The audit observed that it reaches the network. Each of those is consistent with what it says it does. Secrets in the source: none found.

Which assistants does Mcp Builder work with?

Its documentation mentions claude-code and claude-desktop. That is what the text claims, not a compatibility test we ran.

How current is this page?

The grade is for one exact copy of the source (be410003e718), read on 2026-10-12. The repository is watched, and a new audit runs when it changes — this is the first audit.

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