Tech MCP Server Dev

What it does

When your agent uses it

• The user needs to create an MCP server
• Databases to AI agents
• Design tool schemas
• Integrate with Claude Code — even if they say build an MCP server

Example prompts

• “build an MCP server”
• “connect Claude to our database”
• “expose our API to AI”
• “/tech-mcp-server-dev”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

1. 1Atomic operations: Each tool does ONE thing. "search_users" not "search_and_update_users"
2. 2Clear naming: verb_noun format. "get_customer", "create_order", "search_products"
3. 3Descriptive descriptions: Include WHEN to use, not just what it does
4. 4Strict schemas: Define all parameters with types, descriptions, and required/optional
5. 5Meaningful errors: Return error messages the model can understand and act on

What it can do on your machine

Read from SKILL.md and the folder at commit 4e7f4f8. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Shell commands in SKILL.md call:

  • claude

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Tech MCP Server Dev loads about 1.3k tokens when it runs, and up to ~7.4k if it reads all its reference files. Until then it costs about 113 tokens; SKILL.md has 217 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~113

When it runs · the whole SKILL.md, loaded when a task matches

~1.3k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~7.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from asgard-ai-platform/skills at commit 4e7f4f8, republished under its MIT licence (© asgard-ai-platform). 217 words, ~1,312 tokens.

name

tech-mcp-server-dev

description

Build MCP (Model Context Protocol) servers including tool definition, schema design, authentication, error handling, and Claude Code integration. Use this skill when the user needs to create an MCP server, expose APIs or databases to AI agents, design tool schemas, or integrate with Claude Code — even if they say 'build an MCP server', 'connect Claude to our database', 'expose our API to AI', or 'create a tool for Claude Code'.

metadata.category

WP-11 通用技術

metadata.tags

technology, mcp, claude-code, ai-agents

IRON LAW: Tools Must Be Self-Describing

Every MCP tool must have a clear name, description, and input schema
that allows the AI model to understand WHEN and HOW to use it without
any external documentation. If the model can't figure out when to call
your tool from its name and description alone, the tool is poorly designed.

Claude Code / AI Agent
    ↓ (stdio JSON-RPC 2.0)
MCP Server (your code)
    ↓
Your Data Source (DB, API, file system, etc.)

{
  "name": "search_customers",
  "description": "Search for customers by name, email, or phone number. Use when the user asks to find or look up a specific customer.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "query": {
        "type": "string",
        "description": "Search term — can be customer name, email, or phone"
      },
      "limit": {
        "type": "number",
        "description": "Maximum results to return (default: 10)",
        "default": 10
      }
    },
    "required": ["query"]
  }
}

{
  "mcpServers": {
    "my-server": {
      "command": "node",
      "args": ["path/to/server.js"],
      "env": {
        "DATABASE_URL": "${DATABASE_URL}"
      }
    }
  }
}

Tool handler should:
1. Validate input (check required fields, types)
2. Try the operation
3. On success: return structured data (JSON)
4. On error: return { "error": "Human-readable message", "code": "ERROR_CODE" }
   - NOT stack traces or internal error details
   - The MODEL needs to understand the error to retry or inform the user

# MCP Server Spec: {Server Name}

## Purpose
{What data/capability this server exposes}

## Tools
| Tool | Description | Parameters | Returns |
|------|-----------|-----------|---------|
| {name} | {when to use} | {params} | {return type} |

## Data Source
- Type: {database / API / file system}
- Connection: {how to connect}
- Auth: {env vars needed}

## .mcp.json
```json
{config}

## Gotchas

- **Environment variables for secrets**: NEVER hardcode API keys or database passwords. Use `env` in .mcp.json to pass secrets from environment variables.
- **Tool description quality**: The model decides whether to use your tool based SOLELY on the name + description. A bad description means the tool never gets called (or gets called for wrong reasons).
- **Return data size**: Don't return 10,000 rows. The model's context window is limited. Return summarized or paginated results. Default limit = 10-20 items.
- **Idempotent reads, confirmed writes**: Read operations should be safe to call multiple times. Write operations (create, update, delete) should confirm with the user before execution.
- **Test with real model interactions**: Unit tests aren't enough. The real test is whether Claude actually uses your tool correctly in conversation. Test with diverse prompts.

## References

- For MCP SDK documentation, see `references/mcp-sdk.md`
- For advanced MCP patterns (resources, prompts), see `references/mcp-advanced.md`

© asgard-ai-platform, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in tech-mcp-server-dev of asgard-ai-platform/skills.

• SKILL.md
• examples/sample_scenario.md
• references/mcp-advanced.md
• references/mcp-sdk.md

Open the folder on GitHubat commit 4e7f4f8