"Using llama.cpp and Searxng with local models" matching MCP servers:

Classifies development task complexity (LIGHT/MEDIUM/HEAVY) and recommends the most cost-efficient AI model per provider, enabling optimized model selection for coding tasks.

Privacy-focused web search MCP server using SearXNG with Streamable HTTP transport, supporting authentication and advanced search parameters.

An MCP server that integrates the SearXNG API for web search and URL content extraction with advanced features like pagination, caching, and proxy support.

Enables MCP clients to perform web searches through a self-hosted SearXNG instance, offering privacy-focused metasearch without API keys or vendor lock-in.

Enables AI assistants to perform web searches and read URL content via a SearXNG instance.

Provides a bridge between AI assistants and SearXNG, a privacy-respecting metasearch engine, enabling web searches and engine discovery via the Model Context Protocol.

An MCP server that integrates with the SearXNG API to provide comprehensive web search capabilities with features like time filtering, language selection, and safe search. It also enables users to fetch and convert web content from specific URLs into markdown format.

MCP server that lists available GitHub Models and compares responses from multiple models for the same prompt.

A Model Context Protocol server that enables AI assistants to perform web searches using SearXNG, a privacy-respecting metasearch engine.

Enables web search through a SearXNG instance via MCP, returning search result summaries.

A minimal MCP server that exposes a private SearXNG instance as a search tool over streamable-HTTP, enabling web search from the llama.cpp WebUI or any compatible MCP client.

Enables web search through one or two SearxNG instances and retrieval of web pages, GitHub READMEs, and article text via MCP tools.

Enables AI agents to run privacy-friendly web, news, image, and video searches through their own SearXNG instance, with autocomplete, instance/engine discovery, and pagination, language, time-range, SafeSearch, engine, and domain filters. It also fetches pages and returns clean readable text, stripping headers, footers, navigation, sidebars, ads, and comment sections by default while letting the agent re-include them per call.

MCP server that connects to a self-hosted SearXNG instance and exposes web search capabilities over MCP HTTP (JSON-RPC), enabling AI chatbots to search the internet for real-time information.

Enables MCP-capable agents to perform web and news searches and extract readable text from pages through a self-hosted SearXNG instance, with no API key and support for search-and-extract in a single call, including engine fallback for silent zero-result responses.

Provides structured search tools (web, news, images, videos, research) via a SearXNG instance, with direct URL reading disabled by default for security.

Provides LLM-free search, fetch, and rerank tools over any reachable SearXNG instance, returning extracted, deduplicated, cross-encoder-reranked results with citation-ready markers and coverage signals. Lets agent hosts such as Open WebUI, Claude, or tool-calling models drive their own iterative research loop while sharing one deterministic retrieval and ranking core.

An MCP server that integrates the SearXNG API to provide web search with pagination, filtering, and URL content extraction.

An MCP server that helps interact with and compare different GitHub Models, enabling listing, filtering, and comparing model responses.

MCP server that exposes SearXNG search and HTTP fetch tools for AI agents, enabling web search and clean page text extraction via natural language.