"iOS Anti-Debugging Techniques and Implementation" matching MCP servers:

MCP server for web search and URL reading via CLIProxyAPI Antigravity backend, enabling web search, URL content retrieval, and grounded research.

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.

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.

Provides MCP tools for web scraping, including smart fetching, proxy rotation, and browser rendering to bypass anti-bot challenges and render JavaScript-heavy sites.

Python MCP server for vector search using Qdrant vector database and Ollama embeddings, with advanced query techniques like query expansion, HyDE, and reranking.

A server implementation for interacting with Wikidata API using the Model Context Protocol, providing tools for searching identifiers, extracting metadata, and executing SPARQL queries.

A Model Context Protocol (MCP) server implementation that integrates with Firecrawl for advanced web scraping capabilities.

An MCP server implementation that integrates the Tavily Search API, providing optimized search capabilities for LLMs.

An MCP server implementation that enables interaction with the Unstructured API, providing tools to list, create, update, and manage sources, destinations, and workflows.

Nexus Memory gives every MCP-compatible agent one persistent, self-hosted shared memory with hybrid retrieval, drift detection, and anti-poisoning features.

Enables AI agents to retrieve clean, anti-poisoned research context from academic papers, GitHub repositories, and web search, with built-in prompt injection defenses and zero-cost reranking.

Enhances large language models with competitive programming knowledge by leveraging OI-Wiki content through vector search, allowing models to retrieve relevant algorithms and techniques.

A Model Context Protocol implementation that enables large language models to call external tools (like weather forecasts and GitHub information) through a structured protocol, with visualization of the model's reasoning process.

A Model Context Protocol server implementation that provides a standardized interface for interacting with Smallest.ai's knowledge base management system.

A ready-to-use starter implementation of the Model Context Protocol (MCP) server that enables applications to provide standardized context for LLMs with sample resources, tools, and prompts.

Enables MCP clients to search ln-ashlar documentation and review implementation plans via Gemini, with OAuth 2.0 + PKCE authentication.

Enables coding agents to find real iOS app screens, user journeys, and website design systems, including colors, typography, components, and DESIGN.md files, so generated UIs resemble real products instead of AI defaults.

A custom Model Context Protocol implementation that integrates Perplexity AI with Claude Desktop, allowing users to access Perplexity's AI models for both single questions and multi-turn conversations.