evo-scry

MCP server for internet search via direct Google and DuckDuckGo HTML scraping with AI-powered result normalization.

Python. Zero API keys required for search. Optional AI summarization via GitHub Copilot token or local Ollama model.

Features

• 4 MCP Tools: web_search, search_google, search_duckduckgo, extract_content

• Multi-engine aggregation: Parallel search across Google + DuckDuckGo with deduplication and cross-engine ranking

• AI summarization: Optional result summaries via GitHub Copilot or local Ollama models

• Production-ready: Systemd service with full environment variable configuration

• Privacy-respecting: Direct HTML scraping, no third-party search APIs

• FastMCP pattern: Same architecture as evo-mem — SSE + streamable-http dual transport

Related MCP server: webmcp

Quick Start

# Create virtual environment
python3 -m venv .venv
source .venv/bin/activate

# Install
pip install -e .

# Run (STDIO transport for local MCP clients)
python -m evoscry.mcp_server

# Run (SSE transport for remote/systemd)
python -m evoscry.mcp_server --transport sse --port 3000

Claude Desktop / VS Code Configuration

{
  "mcpServers": {
    "evo-scry": {
      "command": "python",
      "args": ["-m", "evoscry.mcp_server"]
    }
  }
}

SSE Transport (remote)

{
  "mcpServers": {
    "evo-scry": {
      "url": "http://your-server:3000/sse"
    }
  }
}

MCP Tools

web_search

Search the internet using both Google and DuckDuckGo. Results are aggregated, deduplicated, and ranked.

search_google / search_duckduckgo

Engine-specific search tools with the same parameters (minus engines and summarize).

extract_content

Fetch URLs and extract clean text or Markdown content.

AI Summarization Setup

GitHub Copilot Token (recommended)

python -m evoscry.generate_copilot_token

Follow the prompts to authenticate via GitHub OAuth Device Flow. Add the generated token to your .env or systemd environment file.

Local Model (Ollama)

# In .env or systemd env:
EVOSCRY_LOCAL_MODEL_URL=http://localhost:11434
EVOSCRY_LOCAL_MODEL_NAME=llama3

Systemd Deployment

# Install (requires root)
sudo bash install.sh

# Configure
sudo vim /etc/evo-scry/evo-scry.env

# Start
sudo systemctl enable --now evo-scry

SSE endpoint: http://localhost:3000/sse Health check: http://localhost:3000/health

Configuration

All options via environment variables. See .env.example for the full list.

License

MIT