Search Memory MCP server

Search Memory MCP

Free web search and long-term memory for your AI assistant. No API keys. Your data stays on your machine.

Works with Claude Desktop, Claude Code, Cursor, Windsurf, and any other MCP client.

Why Search Memory MCP?

• 🔎 Search the web for free. DuckDuckGo, Bing, Brave, and Google, with automatic fallback. No API keys, no subscriptions.
• 📄 Read any page as clean Markdown. Fast paths for GitHub, RSS, and static pages. PDF, DOCX and EPUB links are converted to text. A real browser only when a page needs it.
• 🧠 Remember across sessions. Your assistant can save notes and recall them later.
• 📚 Build a private knowledge base. Index pages and documents, then search them with keyword + semantic search and get answers with citations.
• 🔁 Research that remembers. One research call checks what you already indexed, searches the web, reads the top pages, answers with citations, and keeps the pages for next time. Every source shows when it was published (from page or PDF metadata) and when it was fetched or indexed, so you can tell how current an answer is.
• 🔒 Local first. Cache, memory, index, and models all run on your machine.
• 🛡️ Safer with untrusted pages. Hidden text and invisible characters are removed from fetched pages, and web content is marked as data so the assistant is told not to follow instructions inside it. See SECURITY.md.

Quick start

Add this to your MCP client config (for example claudedesktopconfig.json or .cursor/mcp.json):

{
  "mcpServers": {
    "search-memory": {
      "command": "npx",
      "args": ["-y", "search-memory-mcp@latest"]
    }
  }
}

Restart your client and ask: "Search the web for the latest Node.js release and remember the version number."

Search and most pages work right away. Pages that need a real browser use Playwright Chromium (about 180 MB). It is downloaded during install, or on first use if your package manager skipped install scripts, so that first request can take a few minutes. To download it ahead of time, run npx playwright install chromium. Model-backed features download small local models on first use.

Requires Node.js 20.9 to 25 (Node 24 recommended). If your Node version is newer, or npm skipped install scripts, the server prints the exact fix when it starts. You can also run it in Docker with nothing installed on your machine except Docker.

Run in Docker (no local setup)

Docker brings its own Node 24, SQLite module and Chromium, so it works whatever Node version you have. Point your MCP client at the published image (linux/amd64 and linux/arm64):

{
  "mcpServers": {
    "search-memory": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "-v", "search-memory-data:/app/data", "-v", "search-memory-models:/root/.cache/huggingface", "ghcr.io/kefyusuf/search-memory-mcp:latest"]
    }
  }
}

Docker downloads the image on first start. Run docker pull ghcr.io/kefyusuf/search-memory-mcp:latest to update, or use a version tag such as :1.0 to stay on one release. To build the image yourself instead, run docker build -t search-memory-mcp . in a clone and use search-memory-mcp as the image name.

The named volumes keep your cache, memory, knowledge base and downloaded models between runs. To let ingestdocument read local files, mount the folder and allow it, for example "-v", "/home/me/notes:/notes:ro", "-e", "INGESTALLOWED_DIRS=/notes".

Features

Search & fetch

Shortened. The full README is on GitHub.