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https://github.com/leonvanzyl/autocoder.git
synced 2026-01-30 06:12:06 +00:00
fix: wire MCP server into ExpandChatSession for feature creation
Replace direct-DB feature creation with MCP tool path. The expand session now configures the feature MCP server and allows feature_create_bulk tool calls, matching how AssistantChatSession already works. Removes duplicated _create_features_bulk() method and <features_to_create> regex parsing. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
rudiheydra
@@ -10,8 +10,8 @@ import asyncio
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import json
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import logging
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import os
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import re
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import shutil
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import sys
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import threading
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import uuid
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from datetime import datetime
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@@ -38,6 +38,13 @@ API_ENV_VARS = [
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"ANTHROPIC_DEFAULT_HAIKU_MODEL",
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]
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# Feature MCP tools needed for expand session
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EXPAND_FEATURE_TOOLS = [
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"mcp__features__feature_create",
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"mcp__features__feature_create_bulk",
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"mcp__features__feature_get_stats",
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]
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async def _make_multimodal_message(content_blocks: list[dict]) -> AsyncGenerator[dict, None]:
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"""
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@@ -61,9 +68,8 @@ class ExpandChatSession:
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Unlike SpecChatSession which writes spec files, this session:
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1. Reads existing app_spec.txt for context
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2. Parses feature definitions from Claude's output
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3. Creates features via REST API
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4. Tracks which features were created during the session
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2. Chats with the user to define new features
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3. Claude creates features via the feature_create_bulk MCP tool
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"""
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def __init__(self, project_name: str, project_dir: Path):
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@@ -171,6 +177,18 @@ class ExpandChatSession:
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# This allows using alternative APIs (e.g., GLM via z.ai) that may not support Claude model names
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model = os.getenv("ANTHROPIC_DEFAULT_OPUS_MODEL", "claude-opus-4-5-20251101")
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# Build MCP servers config for feature creation
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mcp_servers = {
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"features": {
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"command": sys.executable,
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"args": ["-m", "mcp_server.feature_mcp"],
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"env": {
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"PROJECT_DIR": str(self.project_dir.resolve()),
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"PYTHONPATH": str(ROOT_DIR.resolve()),
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},
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},
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}
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# Create Claude SDK client
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try:
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self.client = ClaudeSDKClient(
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@@ -181,8 +199,10 @@ class ExpandChatSession:
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allowed_tools=[
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"Read",
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"Glob",
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*EXPAND_FEATURE_TOOLS,
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],
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permission_mode="acceptEdits",
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mcp_servers=mcp_servers,
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permission_mode="bypassPermissions",
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max_turns=100,
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cwd=str(self.project_dir.resolve()),
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settings=str(settings_file.resolve()),
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@@ -267,7 +287,8 @@ class ExpandChatSession:
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"""
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Internal method to query Claude and stream responses.
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Handles text responses and detects feature creation blocks.
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Feature creation is handled by Claude calling the feature_create_bulk
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MCP tool directly -- no text parsing needed.
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"""
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if not self.client:
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return
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@@ -291,9 +312,6 @@ class ExpandChatSession:
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else:
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await self.client.query(message)
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# Accumulate full response to detect feature blocks
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full_response = ""
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# Stream the response
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async for msg in self.client.receive_response():
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msg_type = type(msg).__name__
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@@ -305,7 +323,6 @@ class ExpandChatSession:
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if block_type == "TextBlock" and hasattr(block, "text"):
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text = block.text
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if text:
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full_response += text
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yield {"type": "text", "content": text}
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self.messages.append({
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@@ -314,123 +331,6 @@ class ExpandChatSession:
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"timestamp": datetime.now().isoformat()
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})
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# Check for feature creation blocks in full response (handle multiple blocks)
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features_matches = re.findall(
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r'<features_to_create>\s*(\[[\s\S]*?\])\s*</features_to_create>',
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full_response
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)
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if features_matches:
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# Collect all features from all blocks, deduplicating by name
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all_features: list[dict] = []
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seen_names: set[str] = set()
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for features_json in features_matches:
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try:
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features_data = json.loads(features_json)
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if features_data and isinstance(features_data, list):
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for feature in features_data:
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name = feature.get("name", "")
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if name and name not in seen_names:
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seen_names.add(name)
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all_features.append(feature)
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except json.JSONDecodeError as e:
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logger.error(f"Failed to parse features JSON block: {e}")
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# Continue processing other blocks
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if all_features:
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try:
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# Create all deduplicated features
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created = await self._create_features_bulk(all_features)
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if created:
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self.features_created += len(created)
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self.created_feature_ids.extend([f["id"] for f in created])
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yield {
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"type": "features_created",
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"count": len(created),
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"features": created
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}
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logger.info(f"Created {len(created)} features for {self.project_name}")
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except Exception:
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logger.exception("Failed to create features")
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yield {
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"type": "error",
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"content": "Failed to create features"
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}
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async def _create_features_bulk(self, features: list[dict]) -> list[dict]:
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"""
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Create features directly in the database.
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Args:
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features: List of feature dictionaries with category, name, description, steps
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Returns:
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List of created feature dictionaries with IDs
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Note:
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Uses flush() to get IDs immediately without re-querying by priority range,
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which could pick up rows from concurrent writers.
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"""
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# Import database classes
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import sys
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root = Path(__file__).parent.parent.parent
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if str(root) not in sys.path:
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sys.path.insert(0, str(root))
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from api.database import Feature, create_database
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# Get database session
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_, SessionLocal = create_database(self.project_dir)
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session = SessionLocal()
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try:
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# Determine starting priority
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max_priority_feature = session.query(Feature).order_by(Feature.priority.desc()).first()
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current_priority = (max_priority_feature.priority + 1) if max_priority_feature else 1
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created_rows: list = []
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for f in features:
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db_feature = Feature(
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priority=current_priority,
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category=f.get("category", "functional"),
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name=f.get("name", "Unnamed feature"),
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description=f.get("description", ""),
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steps=f.get("steps", []),
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passes=False,
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in_progress=False,
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)
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session.add(db_feature)
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created_rows.append(db_feature)
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current_priority += 1
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# Flush to get IDs without relying on priority range query
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session.flush()
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# Build result from the flushed objects (IDs are now populated)
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created_features = [
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{
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"id": db_feature.id,
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"name": db_feature.name,
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"category": db_feature.category,
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}
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for db_feature in created_rows
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]
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session.commit()
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return created_features
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except Exception:
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session.rollback()
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raise
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finally:
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session.close()
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def get_features_created(self) -> int:
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"""Get the total number of features created in this session."""
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return self.features_created
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