mcpField
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creating-mcp-servers

creating-mcp-servers

github.com/oaustegardDevelopment15744 installsUpdated 1d ago
Repository

About creating-mcp-servers

A development skill for building MCP servers with FastMCP v2, aimed at server implementers. It covers tool-description optimization, progressive disclosure, and MCPB packaging, with gateway-pattern references.

Key features

  1. 01FastMCP v2 implementation guidance
  2. 02Progressive disclosure and gateway patterns
  3. 03Tool description and annotation optimization
  4. 04Documentation lookup through LLMS_TXT.md
  5. 05Package and validate MCPB files

Use cases

  1. 01Design gateway patterns for related capabilities
  2. 02Reduce tool-description and context overhead
  3. 03Implement servers using FastMCP documentation
  4. 04Package MCP servers as MCPB files

MCP support

The skill guides developers in building MCP servers with FastMCP v2, including tool design, gateway patterns, and MCPB packaging.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/oaustegard/claude-skills --skill creating-mcp-servers

After installing, type/creating-mcp-serversin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

CHANGELOG.md
README.md
references/
GATEWAY_PATTERNS.md
LLMS_TXT.md
MANDATORY_PATTERNS.md
MCPB_BUNDLING.md
PROGRESSIVE_DISCLOSURE.md
scripts/
create_mcpb.py

Details

From the project README

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

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