Fix CI/CD: Add Gitea Actions workflow and fix linting issues
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340
mcp_servers/database_mcp.py
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340
mcp_servers/database_mcp.py
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"""Database MCP Server for 7000%AUTO
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Provides database operations for idea management
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"""
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import logging
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from mcp.server.fastmcp import FastMCP
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logger = logging.getLogger(__name__)
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mcp = FastMCP("Database Server")
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# Database initialization flag for MCP server process
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_db_ready = False
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async def _init_db_if_needed():
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"""Initialize database if not already initialized. MCP servers run in separate processes."""
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global _db_ready
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if not _db_ready:
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try:
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from database.db import init_db
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await init_db()
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_db_ready = True
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logger.info("Database initialized in MCP server")
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except Exception as e:
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logger.error(f"Failed to initialize database in MCP server: {e}")
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raise
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@mcp.tool()
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async def get_previous_ideas(limit: int = 50) -> dict:
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"""
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Get list of previously generated ideas.
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Args:
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limit: Maximum number of ideas to return (default 50)
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Returns:
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Dictionary with list of ideas
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"""
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try:
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await _init_db_if_needed()
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from database import get_db, Idea
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from sqlalchemy import select
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async with get_db() as session:
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query = select(Idea).order_by(Idea.created_at.desc()).limit(limit)
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result = await session.execute(query)
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ideas = result.scalars().all()
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return {
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"success": True,
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"ideas": [
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{
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"id": idea.id,
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"title": idea.title,
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"description": idea.description[:200],
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"source": idea.source,
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"used": idea.used
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}
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for idea in ideas
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],
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"count": len(ideas)
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}
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except Exception as e:
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logger.error(f"Error getting previous ideas: {e}")
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return {"success": False, "error": str(e), "ideas": []}
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@mcp.tool()
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async def check_idea_exists(title: str) -> dict:
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"""
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Check if a similar idea already exists.
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Args:
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title: Title to check for similarity
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Returns:
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Dictionary with exists flag and similar ideas if found
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"""
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try:
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await _init_db_if_needed()
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from database import get_db, Idea
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from sqlalchemy import select
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title_lower = title.lower()
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title_words = set(title_lower.split())
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async with get_db() as session:
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# Get all ideas for comparison
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query = select(Idea)
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result = await session.execute(query)
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ideas = result.scalars().all()
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similar = []
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for idea in ideas:
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idea_title_lower = idea.title.lower()
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idea_words = set(idea_title_lower.split())
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# Check exact match
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if title_lower == idea_title_lower:
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similar.append({
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"id": idea.id,
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"title": idea.title,
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"match_type": "exact"
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})
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continue
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# Check partial match (title contains or is contained)
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if title_lower in idea_title_lower or idea_title_lower in title_lower:
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similar.append({
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"id": idea.id,
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"title": idea.title,
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"match_type": "partial"
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})
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continue
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# Check word overlap (>50%)
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overlap = len(title_words & idea_words)
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total = len(title_words | idea_words)
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if total > 0 and overlap / total > 0.5:
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similar.append({
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"id": idea.id,
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"title": idea.title,
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"match_type": "similar"
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})
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return {
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"success": True,
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"exists": len(similar) > 0,
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"similar_ideas": similar[:5],
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"count": len(similar)
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}
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except Exception as e:
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logger.error(f"Error checking idea existence: {e}")
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return {"success": False, "error": str(e), "exists": False}
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@mcp.tool()
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async def save_idea(title: str, description: str, source: str) -> dict:
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"""
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Save a new idea to the database.
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Args:
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title: Idea title
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description: Idea description
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source: Source of the idea (arxiv, reddit, x, hn, ph)
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Returns:
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Dictionary with saved idea details
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"""
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try:
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await _init_db_if_needed()
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from database import create_idea
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idea = await create_idea(
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title=title,
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description=description,
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source=source
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)
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return {
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"success": True,
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"idea": {
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"id": idea.id,
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"title": idea.title,
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"description": idea.description,
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"source": idea.source,
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"created_at": idea.created_at.isoformat() if idea.created_at else None
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}
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}
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except Exception as e:
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logger.error(f"Error saving idea: {e}")
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return {"success": False, "error": str(e)}
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@mcp.tool()
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async def get_database_stats() -> dict:
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"""
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Get database statistics.
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Returns:
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Dictionary with database stats
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"""
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try:
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await _init_db_if_needed()
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from database import get_stats
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stats = await get_stats()
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return {
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"success": True,
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"stats": stats
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}
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except Exception as e:
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logger.error(f"Error getting database stats: {e}")
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return {"success": False, "error": str(e)}
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@mcp.tool()
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async def submit_idea(
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project_id: int,
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title: str,
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description: str,
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source: str,
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tech_stack: list[str] = None,
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target_audience: str = None,
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key_features: list[str] = None,
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complexity: str = None,
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estimated_time: str = None,
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inspiration: str = None
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) -> dict:
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"""
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Submit a generated project idea. Use this tool to finalize and save your idea.
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The idea will be saved directly to the database for the given project.
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Args:
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project_id: The project ID to associate this idea with (required)
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title: Short project name (required)
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description: Detailed description of the project (required)
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source: Source of inspiration - arxiv, reddit, x, hn, or ph (required)
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tech_stack: List of technologies to use (e.g., ["python", "fastapi"])
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target_audience: Who would use this project
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key_features: List of key features
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complexity: low, medium, or high
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estimated_time: Estimated implementation time (e.g., "2-4 hours")
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inspiration: Brief note on what inspired this idea
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Returns:
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Dictionary with success status
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"""
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try:
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await _init_db_if_needed()
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from database.db import set_project_idea_json
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# Build the complete idea dict
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idea_data = {
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"title": title,
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"description": description,
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"source": source,
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"tech_stack": tech_stack or [],
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"target_audience": target_audience or "",
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"key_features": key_features or [],
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"complexity": complexity or "medium",
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"estimated_time": estimated_time or "",
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"inspiration": inspiration or "",
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}
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# Save to database
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success = await set_project_idea_json(project_id, idea_data)
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if success:
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logger.info(f"Idea submitted for project {project_id}: {title}")
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return {"success": True, "message": f"Idea '{title}' saved successfully"}
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else:
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logger.error(f"Project {project_id} not found")
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return {"success": False, "error": f"Project {project_id} not found"}
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except Exception as e:
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logger.error(f"Error submitting idea: {e}")
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return {"success": False, "error": str(e)}
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@mcp.tool()
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async def submit_plan(
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project_id: int,
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project_name: str,
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overview: str,
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display_name: str = None,
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tech_stack: dict = None,
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file_structure: dict = None,
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features: list[dict] = None,
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implementation_steps: list[dict] = None,
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testing_strategy: dict = None,
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configuration: dict = None,
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error_handling: dict = None,
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readme_sections: list[str] = None
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) -> dict:
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"""
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Submit an implementation plan. Use this tool to finalize your project plan.
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The plan will be saved directly to the database for the given project.
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Args:
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project_id: The project ID to associate this plan with (required)
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project_name: kebab-case project name (required)
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overview: 2-3 sentence summary of what will be built (required)
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display_name: Human readable project name
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tech_stack: Technology stack details with language, runtime, framework, key_dependencies
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file_structure: File structure with root_files and directories
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features: List of features with name, priority, description, implementation_notes
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implementation_steps: Ordered list of implementation steps
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testing_strategy: Testing approach with unit_tests, integration_tests, test_files, test_commands
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configuration: Config details with env_variables and config_files
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error_handling: Error handling strategies
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readme_sections: List of README section titles
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Returns:
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Dictionary with success status
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"""
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try:
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await _init_db_if_needed()
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from database.db import set_project_plan_json
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# Build the complete plan dict
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plan_data = {
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"project_name": project_name,
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"display_name": display_name or project_name.replace("-", " ").title(),
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"overview": overview,
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"tech_stack": tech_stack or {},
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"file_structure": file_structure or {},
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"features": features or [],
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"implementation_steps": implementation_steps or [],
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"testing_strategy": testing_strategy or {},
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"configuration": configuration or {},
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"error_handling": error_handling or {},
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"readme_sections": readme_sections or []
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}
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# Save to database
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success = await set_project_plan_json(project_id, plan_data)
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if success:
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logger.info(f"Plan submitted for project {project_id}: {project_name}")
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return {"success": True, "message": f"Plan '{project_name}' saved successfully"}
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else:
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logger.error(f"Project {project_id} not found")
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return {"success": False, "error": f"Project {project_id} not found"}
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except Exception as e:
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logger.error(f"Error submitting plan: {e}")
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return {"success": False, "error": str(e)}
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if __name__ == "__main__":
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mcp.run()
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