mcp-builder-example-1-database-query-tool
Sub-skill of mcp-builder: Example 1: Database Query Tool (+1).
Best use case
mcp-builder-example-1-database-query-tool is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of mcp-builder: Example 1: Database Query Tool (+1).
Teams using mcp-builder-example-1-database-query-tool should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/example-1-database-query-tool/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How mcp-builder-example-1-database-query-tool Compares
| Feature / Agent | mcp-builder-example-1-database-query-tool | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of mcp-builder: Example 1: Database Query Tool (+1).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Example 1: Database Query Tool (+1)
## Example 1: Database Query Tool
```typescript
server.setRequestHandler(CallToolRequestSchema, async (request) => {
if (request.params.name === "query_database") {
const { sql, params } = request.params.arguments;
const result = await db.query(sql, params);
return { content: [{ type: "text", text: JSON.stringify(result, null, 2) }] };
}
});
```
## Example 2: API Integration
```typescript
server.setRequestHandler(CallToolRequestSchema, async (request) => {
if (request.params.name === "fetch_weather") {
const { city } = request.params.arguments;
const response = await fetch(`https://api.weather.com/v1/${city}`);
const data = await response.json();
return { content: [{ type: "text", text: `Temperature: ${data.temp}F` }] };
}
});
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