django-silk-mcp 0.1.5

MCP server exposing django-silk profiling data as AI assistant tools

django-silk-mcp

An MCP server that exposes django-silk profiling data as tools for any MCP-compatible AI coding assistant. Enables query-level investigation and optimization directly from your conversation — N+1 detection, EXPLAIN ANALYZE, over-fetch analysis, and Python profiling without leaving your editor.

Installation

pip install django-silk-mcp
# or
uv add django-silk-mcp

Configuration

1. Add to INSTALLED_APPS

INSTALLED_APPS = [
    ...
    "silk",
    "django_silk_mcp",
]

2. Configure your MCP client

Expose the MCP server as a URL inside your Django app. Works on both WSGI and ASGI with no extra infrastructure.

Add to your root urls.py:

urlpatterns = [
    ...
    path("silk/", include("silk.urls", namespace="silk")),
    path("silk/mcp", include("django_silk_mcp.urls")),
]

This serves the MCP endpoint at /silk/mcp. The MCP server runs as part of your Django app — no separate process needed, it shares the same port as your dev server. Then configure your MCP client:

Claude Code:

claude mcp add silk-mcp --transport http http://localhost:8000/silk/mcp

Cursor: Go to Settings → Toos & MCPs → New MCP Server and add a new server with the following configuration:

{
  "mcpServers": {
    "silk-mcp": {
      "url": "http://localhost:8000/silk/mcp"
    }
  }
}

The same URL works with any MCP-compatible AI tool.

Tools

Tool	Purpose
get_most_expensive_endpoints	Rank all endpoints by average DB time
get_request_time_breakdown	DB% vs Python% — confirm where time is spent
get_duplicate_queries	Detect N+1 patterns
get_query_sources	Which code lines triggered each query
get_overfetched_fields	SQL columns vs serializer fields — .only() candidates
explain_slow_queries	EXPLAIN (ANALYZE, BUFFERS) on slow SELECTs
get_request_queries	All SQL for a specific request
get_slow_queries	Slowest individual queries across all requests
get_slow_requests	Slowest HTTP requests
compare_requests	Before/after comparison with burst deduplication
get_python_profiles	@silk_profile decorated block timings
get_cprofile_hotspots	cProfile hotspots — no decorators needed

Usage

# Hit an endpoint first so Silk has data
curl http://localhost:8000/api/your-endpoint/

# Then ask your AI assistant
# "What are the slowest endpoints?"
# "Find N+1 queries in /api/your-endpoint/"
# "Run EXPLAIN on the slow queries for /api/your-endpoint/"