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Refactor MCP server structure and add separate project tools
- Rename src/mcp to src/mcp_server for clarity - Update all internal imports to use new path - Create features/projects directory for modular tool organization - Add separate, simple project tools (create, list, get, delete, update) - Keep consolidated tools for backward compatibility (via env var) - Add USE_SEPARATE_PROJECT_TOOLS env var to toggle between approaches The new separate tools: - Solve the async project creation context loss issue - Provide clearer, single-purpose interfaces - Remove complex PRP examples for simplicity - Handle project creation polling automatically
This commit is contained in:
Rasmus Widing
197
python/src/mcp_server/modules/rag_module.py
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197
python/src/mcp_server/modules/rag_module.py
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"""
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RAG Module for Archon MCP Server (HTTP-based version)
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This module provides tools for:
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- RAG query and search
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- Source management
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- Code example extraction and search
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This version uses HTTP calls to the server service instead of importing
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service modules directly, enabling true microservices architecture.
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"""
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import json
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import logging
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import os
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from urllib.parse import urljoin
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import httpx
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from mcp.server.fastmcp import Context, FastMCP
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# Import service discovery for HTTP communication
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from src.server.config.service_discovery import get_api_url
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logger = logging.getLogger(__name__)
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def get_setting(key: str, default: str = "false") -> str:
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"""Get a setting from environment variable."""
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return os.getenv(key, default)
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def get_bool_setting(key: str, default: bool = False) -> bool:
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"""Get a boolean setting from environment variable."""
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value = get_setting(key, "false" if not default else "true")
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return value.lower() in ("true", "1", "yes", "on")
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def register_rag_tools(mcp: FastMCP):
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"""Register all RAG tools with the MCP server."""
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@mcp.tool()
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async def get_available_sources(ctx: Context) -> str:
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"""
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Get list of available sources in the knowledge base.
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Returns:
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JSON string with structure:
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- success: bool - Operation success status
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- sources: list[dict] - Array of source objects
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- count: int - Number of sources
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- error: str - Error description if success=false
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"""
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try:
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api_url = get_api_url()
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timeout = httpx.Timeout(30.0, connect=5.0)
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async with httpx.AsyncClient(timeout=timeout) as client:
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response = await client.get(urljoin(api_url, "/api/rag/sources"))
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if response.status_code == 200:
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result = response.json()
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sources = result.get("sources", [])
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return json.dumps(
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{"success": True, "sources": sources, "count": len(sources)}, indent=2
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)
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else:
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error_detail = response.text
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return json.dumps(
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{"success": False, "error": f"HTTP {response.status_code}: {error_detail}"},
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indent=2,
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)
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except Exception as e:
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logger.error(f"Error getting sources: {e}")
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return json.dumps({"success": False, "error": str(e)}, indent=2)
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@mcp.tool()
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async def perform_rag_query(
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ctx: Context, query: str, source_domain: str = None, match_count: int = 5
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) -> str:
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"""
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Search knowledge base for relevant content using RAG.
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Args:
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query: Search query
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source_domain: Optional domain filter (e.g., 'docs.anthropic.com').
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Note: This is a domain name, not the source_id from get_available_sources.
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match_count: Max results (default: 5)
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Returns:
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JSON string with structure:
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- success: bool - Operation success status
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- results: list[dict] - Array of matching documents with content and metadata
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- reranked: bool - Whether results were reranked
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- error: str|null - Error description if success=false
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"""
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try:
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api_url = get_api_url()
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timeout = httpx.Timeout(30.0, connect=5.0)
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async with httpx.AsyncClient(timeout=timeout) as client:
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request_data = {"query": query, "match_count": match_count}
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if source_domain:
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request_data["source"] = source_domain
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response = await client.post(urljoin(api_url, "/api/rag/query"), json=request_data)
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if response.status_code == 200:
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result = response.json()
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return json.dumps(
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{
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"success": True,
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"results": result.get("results", []),
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"reranked": result.get("reranked", False),
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"error": None,
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},
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indent=2,
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)
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else:
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error_detail = response.text
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return json.dumps(
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{
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"success": False,
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"results": [],
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"error": f"HTTP {response.status_code}: {error_detail}",
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},
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indent=2,
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)
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except Exception as e:
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logger.error(f"Error performing RAG query: {e}")
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return json.dumps({"success": False, "results": [], "error": str(e)}, indent=2)
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@mcp.tool()
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async def search_code_examples(
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ctx: Context, query: str, source_domain: str = None, match_count: int = 5
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) -> str:
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"""
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Search for relevant code examples in the knowledge base.
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Args:
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query: Search query
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source_domain: Optional domain filter (e.g., 'docs.anthropic.com').
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Note: This is a domain name, not the source_id from get_available_sources.
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match_count: Max results (default: 5)
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Returns:
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JSON string with structure:
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- success: bool - Operation success status
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- results: list[dict] - Array of code examples with content and summaries
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- reranked: bool - Whether results were reranked
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- error: str|null - Error description if success=false
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"""
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try:
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api_url = get_api_url()
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timeout = httpx.Timeout(30.0, connect=5.0)
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async with httpx.AsyncClient(timeout=timeout) as client:
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request_data = {"query": query, "match_count": match_count}
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if source_domain:
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request_data["source"] = source_domain
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# Call the dedicated code examples endpoint
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response = await client.post(
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urljoin(api_url, "/api/rag/code-examples"), json=request_data
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)
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if response.status_code == 200:
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result = response.json()
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return json.dumps(
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{
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"success": True,
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"results": result.get("results", []),
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"reranked": result.get("reranked", False),
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"error": None,
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},
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indent=2,
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)
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else:
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error_detail = response.text
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return json.dumps(
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{
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"success": False,
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"results": [],
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"error": f"HTTP {response.status_code}: {error_detail}",
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},
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indent=2,
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)
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except Exception as e:
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logger.error(f"Error searching code examples: {e}")
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return json.dumps({"success": False, "results": [], "error": str(e)}, indent=2)
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# Log successful registration
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logger.info("✓ RAG tools registered (HTTP-based version)")
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