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

Enables searching, comparing, and inspecting AI models by pricing, context window, and capabilities via the models.dev catalog.

Privacy-respecting web search MCP server for AI assistants using SearXNG, with web search, URL reading, instance failover, and caching.

Enables privacy-friendly web searches through the SearXNG engine, with support for multiple engines, categories, languages, time ranges, and configurable result counts.

An MCP server for connecting agentic systems to search systems via searXNG.

An MCP server for SearXNG that provides web search capabilities with concise model-visible output while preserving full result payloads in metadata. It supports search, parallel fetching, URL extraction, and research workflows through both local stdio and streamable HTTP transports.

An MCP server implementation that integrates the SearxNG API, providing web search capabilities.

Provides web search capabilities using SearxNG, allowing AI assistants like Claude to search the web with a privacy-respecting metasearch engine.

Enables AI agents to look up facts about notable machine-learning models — organization, release date, parameter count, training-compute (FLOP) estimate, hardware and accessibility — by name, and to search or aggregate them by organization, domain, year, or compute threshold. Supports filtering the dataset newest-first and producing per-year training-compute trends, keylessly and without authentication.

Integrates SearXNG API to give AI assistants web search and URL reading capabilities.

Enables users to choose among seven decision-making frameworks and work through them step by step with their own situation, ending with one clear decision and a next action. It also chains multiple frameworks for larger decisions and provides model guides and recommendations.

Enables privacy-preserving web search and content extraction through a self-hosted SearXNG instance, aggregating 70+ engines and converting pages to Markdown for LLM use.

Integrates with SearXNG metasearch engine to provide powerful web search capabilities across multiple search engines with filtering options for categories, languages, time ranges, and safe search levels. Enables comprehensive web searches, autocomplete suggestions, and search engine configuration access through MCP-compatible applications.

Enables privacy-respecting web searches through SearXNG metasearch engine with customizable parameters like language, time range, categories, and engines. Supports safe search levels, pagination control, and basic authentication for secure search operations.

Enables MCP-compatible clients to perform web searches through a self-hosted SearXNG instance, with support for configurable languages, categories, time ranges, and safe search settings.

Enables web search, image search, and news search through a self-hosted SearXNG instance. Provides privacy-focused meta-search capabilities aggregating results from multiple search engines.

Enables clients to list available tools and run searches against a configured SearXNG instance, returning JSON results over either STDIO or HTTP transports.

An MCP server that acts as a bridge to SearXNG instances, allowing AI models to perform web searches with privacy-focused search tools. It supports both STDIO and HTTP transports, featuring built-in rate limiting and session management.

A server that enables language models to perform web searches through SearXNG using the Model Context Protocol standard.

Enables AI agents to perform privacy-respecting web searches through SearXNG, with support for multiple search engines, categories, and advanced filtering options.

Enables AI assistants to perform privacy-respecting web searches, read URLs, retrieve query suggestions, and inspect search-instance capabilities through the Model Context Protocol.