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creating-mcp-servers

Creates production-ready MCP servers using FastMCP v2. Use when building MCP servers, optimizing tool descriptions for context efficiency, implementing progressive disclosure for multiple capabilities, or packaging servers for distribution.

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설치 방법 보기

포함된 파일(9)

  • SKILL.md5.2 KB
  • CHANGELOG.md904 B
  • README.md265 B
  • references/GATEWAY_PATTERNS.md14.9 KB
  • references/LLMS_TXT.md20.2 KB
  • references/MANDATORY_PATTERNS.md6.5 KB
  • references/MCPB_BUNDLING.md4.6 KB
  • references/PROGRESSIVE_DISCLOSURE.md6.8 KB
  • scripts/create_mcpb.py11.5 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Creating MCP Servers

Build production-ready MCP servers using FastMCP v2 with optimal context efficiency through progressive disclosure patterns.

Core Capabilities

  1. Apply the core patterns - Four requirements for consistency
  2. Implement progressive disclosure - Gateway patterns achieving 85-93% token reduction
  3. Optimize tool descriptions - 65-70% token reduction through proper patterns
  4. Bundle servers - Package as MCPB files with validation
  5. Proven gateway patterns - Three complete implementations (Skills, API, Query)

Architecture Decision

1-3 simple tools?
  → Standard FastMCP with optimized tools
  Load: references/MANDATORY_PATTERNS.md

5+ related capabilities?
  → Gateway pattern (progressive disclosure)
  Load: references/PROGRESSIVE_DISCLOSURE.md
  Load: references/GATEWAY_PATTERNS.md

Optimize existing server?
  → Apply mandatory patterns
  Load: references/MANDATORY_PATTERNS.md

Package for distribution?
  → MCPB bundler
  Load: references/MCPB_BUNDLING.md
  Execute: scripts/create_mcpb.py

Need FastMCP documentation?
  → Search references/LLMS_TXT.md for relevant URLs
  → Use web_fetch on gofastmcp.com URLs

Mandatory Patterns (Summary)

Every implementation should meet these four requirements:

  1. uv (never pip) - uv pip install fastmcp
  2. Optimized tool descriptions - Annotations, Annotated, concise docstrings
  3. Authoritative documentation - Fetch from gofastmcp.com via LLMS_TXT.md index
  4. Apply all patterns - Every implementation meets verification checklist

Details in references/MANDATORY_PATTERNS.md

Documentation Retrieval Workflow

To fetch FastMCP documentation:

1. Read references/LLMS_TXT.md - complete URL index
2. Search for relevant topic keywords
3. Use web_fetch on matched URLs (append .md for markdown)
4. Apply patterns from fetched documentation

Example: Authentication patterns → Search LLMS_TXT.md for "authentication" → web_fetch https://gofastmcp.com/servers/auth/authentication.md

Progressive Disclosure Pattern

For servers with 5+ capabilities:

Three-tier loading:

  1. Metadata (~20 tokens/capability) - Always loaded
  2. Content (~500 tokens) - Load on demand
  3. Execution (0 tokens) - Execute without loading

Achieves 85-93% baseline reduction. See references/PROGRESSIVE_DISCLOSURE.md

Implementation Phases

Phase 1: Research

Read LLMS_TXT.md → Find relevant URLs → web_fetch documentation

Phase 2: Implement

Load appropriate reference based on architecture decision. Apply all four patterns.

Phase 3: Package (Optional)

cd /home/claude
zip -r server-name.mcpb manifest.json server.py README.md
cp server-name.mcpb /mnt/user-data/outputs/

See references/MCPB_BUNDLING.md for manifest format.

Reference Library

Documentation index (load first for FastMCP knowledge):

Core patterns:

Implementation:

Scripts:

  • scripts/create_mcpb.py - Bundle MCP servers into .mcpb files

Verification Checklist

Before completing any FastMCP implementation:

✓ Uses uv (not pip)
✓ FastMCP docs fetched from LLMS_TXT.md URLs (not web_search)
✓ Tool annotations (readOnlyHint, title, openWorldHint)
✓ Annotated parameters with Field
✓ Single-sentence docstrings
✓ 65-70% token reduction vs verbose
✓ Server instructions concise (<100 chars)

For gateway implementations, additionally verify:

✓ 85%+ baseline context reduction
✓ Discover returns metadata only
✓ Load fetches content on demand
✓ Execute runs without context cost

Tool Description Pattern

Before (180 tokens):

@mcp.tool()
async def search_items(query: str):
    """Search for items in the database.
    This tool allows comprehensive searching..."""

After (55 tokens):

@mcp.tool(
    annotations={"title": "Search", "readOnlyHint": True, "openWorldHint": False}
)
async def search_items(
    query: Annotated[str, Field(description="Search text")],
    ctx: Context = None
):
    """Search items. Fast full-text search across all fields."""

Common Pitfalls

❌ Using mcpb pack CLI (causes crashes, just use zip)
❌ Using pip instead of uv
❌ web_search for FastMCP docs (use web_fetch on LLMS_TXT.md URLs)
❌ Verbose tool descriptions
❌ Missing tool annotations
❌ Gateway for 1-3 tools (overhead exceeds benefit)
❌ Mixing unrelated capabilities in single gateway

리뷰

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