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

MCP server for local web search via SearXNG, providing unlimited queries without API keys or cost, with automatic fallback to public instances.

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

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

A minimal MCP server that exposes a run_command tool over stdio, enabling command execution within a Docker container.

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

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 for SearXNG that provides LLM agents with advanced search tools, including engine and category targeting, multi-page fanout, and dynamic descriptions from the live engine pool.

MCP server for private web search via self-hosted SearXNG with local reranking, full-page content fetching via Firecrawl, and optional Ollama-powered query expansion and summaries.

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

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

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

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.

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.

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.

An MCP server that wraps a local SearXNG instance to provide private, customizable web search capabilities. It enables AI assistants to perform queries with support for specific parameters like results limits, language, and time ranges.

Enables AI harnesses to maintain a persistent memory layer backed by a local SQLite file, providing MCP tools to add, search, deprecate, and synchronize facts without deleting history.