"Managing Docker Containers and Applications" matching MCP servers:

Provides a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.

A multi-tool AI assistant system that uses Model Context Protocol to connect language models with various tools, including math calculations and weather information.

Provides structured dealer brand data including inventory, promotions, reviews, and dealer profile via MCP tools, enabling LLMs to answer accurate brand-related queries.

Enables querying Kapa.ai's documentation and Q&A capabilities for any project enrolled with Kapa, with tools for asking questions and searching sources.

A meta-MCP server that acts as a universal gateway, allowing users to discover and execute tools from thousands of other MCP servers through semantic search. It dynamically loads servers on demand and provides standardized functions for searching, discovering, and running tools across the entire MCP ecosystem.

Enables coding agents to connect to a user's DevVault, allowing them to search, retrieve, save, and append research/context containers directly from the agent.

heroicons-mcp is a Model Context Protocol (MCP) server that exposes Heroicons. It allows LLMs and agentic applications to search, list, and generate usage examples of icons in React applications.

Enables natural language interactions with Algolia search and analytics APIs through Claude Desktop. Supports searching indices, managing data, analyzing metrics, monitoring performance, and visualizing insights across your Algolia applications.

Enables turning any collection of documentation into a private, semantically searchable MCP endpoint, with one URL per project and self-hosted in a single Docker container.

Enhances LLM applications with deep autonomous web research capabilities, delivering higher quality information than standard search tools by exploring and validating numerous trusted sources.

Connect to your Crawl4AI docker API server.

A utility that integrates Model Context Protocol (MCP) into Express applications, offering both stateful session management and stateless request handling options.

Search Google and major search engines through Talordata SERP API for AI agents and RAG workflows.

Provides a shared, persistent memory layer for AI agents, enabling them to recall, memorize, and review user information across different applications.

Provides AI agents with complete web search, crawling, and RAG capabilities through a Docker-based solution combining Model Context Protocol, Crawl4AI, SearXNG, and Supabase.

A Python implementation of the Model Context Protocol that enables applications to provide standardized context for LLMs, allowing developers to build servers that expose data and functionality to LLM applications.

A unified Docker container that runs Qdrant vector database and provides REST API and MCP interfaces for vector storage and semantic search, compatible with Claude vector hooks.

MCP server providing tools for entity extraction, query refinement, and relevance checking to build Agentic RAG applications.

FastMCP is a comprehensive MCP server allowing secure and standardized data and functionality exposure to LLM applications, offering resources, tools, and prompt management for efficient LLM interactions.

MCP server for MeiliSearch that enables searching indexes, managing documents and indexes, checking health/stats, and managing API keys. Perfect for AI agents to interact with MeiliSearch through natural language.