Files
skill-seekers-reference/src/skill_seekers/mcp/server.py
yusyus 1298f7bd57 feat: C3.4 Configuration Pattern Extraction with AI Enhancement
Add comprehensive AI enhancement to C3.4 Configuration Pattern Extraction
similar to C3.3's dual-mode architecture (API + LOCAL).

NEW CAPABILITIES (What users can do now):
1. **AI-Powered Config Analysis** - Understand what configs do, not just extract them
   - Explanations: What each configuration setting does
   - Best Practices: Suggested improvements and better organization
   - Security Analysis: Identifies hardcoded secrets, exposed credentials
   - Migration Suggestions: Opportunities to consolidate configs
   - Context: Explains detected patterns and when to use them

2. **Dual-Mode AI Support** (Same as C3.3):
   - API Mode: Claude API analyzes configs (requires ANTHROPIC_API_KEY)
   - LOCAL Mode: Claude Code CLI (FREE, no API key needed)
   - AUTO Mode: Automatically detects best available mode

3. **Seamless Integration**:
   - CLI: --enhance, --enhance-local, --ai-mode flags
   - Codebase Scraper: Works with existing enhance_with_ai parameter
   - MCP Tools: Enhanced extract_config_patterns with AI parameters
   - Optional: Enhancement only runs when explicitly requested

Components Added:
- ConfigEnhancer class (~400 lines) - Dual-mode AI enhancement engine
- Enhanced CLI flags in config_extractor.py
- AI integration in codebase_scraper.py config extraction workflow
- MCP tool parameter expansion (enhance, enhance_local, ai_mode)
- FastMCP server tool signature updates
- Comprehensive documentation in CHANGELOG.md and README.md

Performance:
- Basic extraction: ~3 seconds for 100 config files
- With AI enhancement: +30-60 seconds (LOCAL mode, FREE)
- With AI enhancement: +20-40 seconds (API mode, ~$0.10-0.20)

Use Cases:
- Security audits: Find hardcoded secrets across all configs
- Migration planning: Identify consolidation opportunities
- Onboarding: Understand what each config file does
- Best practices: Get improvement suggestions for config organization

Technical Details:
- Structured JSON prompts for reliable AI responses
- 5 enhancement categories: explanations, best_practices, security, migration, context
- Graceful fallback if AI enhancement fails
- Security findings logged separately for visibility
- Results stored in JSON under 'ai_enhancements' key

Testing:
- 28 comprehensive tests in test_config_extractor.py
- Tests cover: file detection, parsing, pattern detection, enhancement modes
- All integrations tested: CLI, codebase_scraper, MCP tools

Documentation:
- CHANGELOG.md: Complete C3.4 feature description
- README.md: Updated C3.4 section with AI enhancement
- MCP tool descriptions: Added AI enhancement details

Related Issues: #74

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-01-04 20:54:07 +03:00

225 lines
8.5 KiB
Python

#!/usr/bin/env python3
"""
Skill Seeker MCP Server - Compatibility Shim
This file provides backward compatibility by delegating to the new server_fastmcp.py implementation.
For new installations, use server_fastmcp.py directly:
python -m skill_seekers.mcp.server_fastmcp
This shim will be deprecated in v3.0.0 (6+ months after v2.4.0 release).
"""
import sys
import warnings
# Show deprecation warning (can be disabled with PYTHONWARNINGS=ignore)
warnings.warn(
"The legacy server.py is deprecated and will be removed in v3.0.0. "
"Please update your MCP configuration to use 'server_fastmcp' instead:\n"
" OLD: python -m skill_seekers.mcp.server\n"
" NEW: python -m skill_seekers.mcp.server_fastmcp\n"
"The new server provides the same functionality with improved performance.",
DeprecationWarning,
stacklevel=2
)
# Re-export tool functions for backward compatibility with tests
try:
from skill_seekers.mcp.tools.config_tools import (
generate_config as generate_config_tool,
list_configs as list_configs_tool,
validate_config as validate_config_tool,
)
from skill_seekers.mcp.tools.scraping_tools import (
estimate_pages_tool,
scrape_docs_tool,
scrape_github_tool,
scrape_pdf_tool,
detect_patterns_tool,
extract_config_patterns_tool,
run_subprocess_with_streaming,
)
from skill_seekers.mcp.tools.packaging_tools import (
package_skill_tool,
upload_skill_tool,
install_skill_tool,
)
from skill_seekers.mcp.tools.splitting_tools import (
split_config as split_config_tool,
generate_router as generate_router_tool,
)
from skill_seekers.mcp.tools.source_tools import (
fetch_config_tool,
submit_config_tool,
add_config_source_tool,
list_config_sources_tool,
remove_config_source_tool,
)
# For test compatibility - create call_tool router function
async def call_tool(name: str, arguments: dict):
"""Route tool calls to appropriate handlers (backward compatibility)."""
from mcp.types import TextContent
try:
if name == "generate_config":
return await generate_config_tool(arguments)
elif name == "estimate_pages":
return await estimate_pages_tool(arguments)
elif name == "scrape_docs":
return await scrape_docs_tool(arguments)
elif name == "package_skill":
return await package_skill_tool(arguments)
elif name == "upload_skill":
return await upload_skill_tool(arguments)
elif name == "list_configs":
return await list_configs_tool(arguments)
elif name == "validate_config":
return await validate_config_tool(arguments)
elif name == "split_config":
return await split_config_tool(arguments)
elif name == "generate_router":
return await generate_router_tool(arguments)
elif name == "scrape_pdf":
return await scrape_pdf_tool(arguments)
elif name == "scrape_github":
return await scrape_github_tool(arguments)
elif name == "fetch_config":
return await fetch_config_tool(arguments)
elif name == "submit_config":
return await submit_config_tool(arguments)
elif name == "add_config_source":
return await add_config_source_tool(arguments)
elif name == "list_config_sources":
return await list_config_sources_tool(arguments)
elif name == "remove_config_source":
return await remove_config_source_tool(arguments)
elif name == "install_skill":
return await install_skill_tool(arguments)
elif name == "detect_patterns":
return await detect_patterns_tool(arguments)
elif name == "extract_config_patterns":
return await extract_config_patterns_tool(arguments)
else:
return [TextContent(type="text", text=f"Unknown tool: {name}")]
except Exception as e:
return [TextContent(type="text", text=f"Error: {str(e)}")]
# For test compatibility - create a mock list_tools function
async def list_tools():
"""Mock list_tools for backward compatibility with tests."""
from mcp.types import Tool
tools = [
Tool(
name="generate_config",
description="Generate config file",
inputSchema={"type": "object", "properties": {}}
),
Tool(
name="list_configs",
description="List available configs",
inputSchema={"type": "object", "properties": {}}
),
Tool(
name="validate_config",
description="Validate config file",
inputSchema={"type": "object", "properties": {}}
),
Tool(
name="estimate_pages",
description="Estimate page count",
inputSchema={"type": "object", "properties": {}}
),
Tool(
name="scrape_docs",
description="Scrape documentation",
inputSchema={"type": "object", "properties": {}}
),
Tool(
name="scrape_github",
description="Scrape GitHub repository",
inputSchema={"type": "object", "properties": {}}
),
Tool(
name="scrape_pdf",
description="Scrape PDF file",
inputSchema={"type": "object", "properties": {}}
),
Tool(
name="package_skill",
description="Package skill into .zip",
inputSchema={"type": "object", "properties": {}}
),
Tool(
name="upload_skill",
description="Upload skill to Claude",
inputSchema={"type": "object", "properties": {}}
),
Tool(
name="install_skill",
description="Install skill",
inputSchema={"type": "object", "properties": {}}
),
Tool(
name="split_config",
description="Split large config",
inputSchema={"type": "object", "properties": {}}
),
Tool(
name="generate_router",
description="Generate router skill",
inputSchema={"type": "object", "properties": {}}
),
Tool(
name="fetch_config",
description="Fetch config from source",
inputSchema={"type": "object", "properties": {}}
),
Tool(
name="submit_config",
description="Submit config to community",
inputSchema={"type": "object", "properties": {}}
),
Tool(
name="add_config_source",
description="Add config source",
inputSchema={"type": "object", "properties": {}}
),
Tool(
name="list_config_sources",
description="List config sources",
inputSchema={"type": "object", "properties": {}}
),
Tool(
name="remove_config_source",
description="Remove config source",
inputSchema={"type": "object", "properties": {}}
),
Tool(
name="extract_config_patterns",
description="Extract configuration patterns from config files",
inputSchema={"type": "object", "properties": {}}
),
]
return tools
except ImportError:
# If imports fail, provide empty stubs
pass
# Delegate to the new FastMCP implementation
if __name__ == "__main__":
try:
from skill_seekers.mcp import server_fastmcp
# Run the new server
server_fastmcp.main()
except ImportError as e:
print(f"❌ Error: Could not import server_fastmcp: {e}", file=sys.stderr)
print("Ensure the package is installed correctly:", file=sys.stderr)
print(" pip install -e .", file=sys.stderr)
sys.exit(1)
except Exception as e:
print(f"❌ Error running server: {e}", file=sys.stderr)
sys.exit(1)