Local MCP Server

Local MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. Agent-friendly local web search using SearXNG for snippets and Crawl4AI for full-text retrieval.

What you get

Local Web Search gives AI agents a local web-search backend with two familiar tools:

• Agents see normal tool names: web_search for discovery and web_fetch for
• Search results stay compact, which keeps context windows cleaner
• Full page fetches are deliberate, cached, and bounded by character limits
• Execution happens in your local environment, pointed at your local SearXNG

Setting it up

local-web-search on PyPI is all you need. Most clients run it directly, so configuration is a few lines and a restart.

Configuration and credentials

You will need 2 environment variables: SEARXNG_BASE_URL, LOCAL_WEB_SEARCH_SEARXNG_HOST. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.

Choosing this one

Among the search and retrieval options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. It is maintained by Local Web Search contributors; worth a glance at recent repository activity before you build anything load-bearing on it.

SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.

Before you rely on it

• It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
• Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
• MCP clients confirm each tool call by default. Leave that on until you have watched what the local mcp server does with a few real requests.