"Information or resources about security" matching MCP servers:

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

Enables AI agents to interact with Google NotebookLM and Gemini API for document analysis, deep research, and notebook creation with enterprise-grade security including post-quantum encryption and 14 security layers.

An MCP server that implements Retrieval-Augmented Generation to efficiently retrieve and process important information from various sources, providing accurate and contextually relevant responses.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Give your AI agents access to 8,500+ community curated awesome lists with over 1 million curated resources.

Enables AI assistants to search and ask questions about documents stored in AnythingLLM workspaces through MCP tools.

Enables AI assistants to search and retrieve transcripts from the Entra.Chat podcast about Microsoft Entra ID, with timestamped YouTube links and guest information.

Lets AI agents search and read a folder of Markdown documentation at query time, exposing heading-level search, whole-page or section retrieval, and page listing as tools and resources over stdio or Streamable HTTP. Can run as a CLI, a hosted endpoint, or a library inside an existing Node or Next.js site.

Description: Persistent memory for AI agents with rollback, audit trails, semantic search, and knowledge graph. Zero-config local SQLite or cloud API. 23 tools, 6 resources, 3 prompts.

An MCP server that retrieves contextual information from company resources and surfaces it to coding agents as rules, reasoning, skills, and commands.

Enables AI agents to record, recall, correct, and forget evidence-backed factual claims with temporal history, while explaining whether remembered information is current, historical, or contested.

Enables access to the Hugging Face Hub API to search and retrieve information about machine learning models, datasets, and their metadata. Provides comprehensive tools for exploring the Hugging Face ecosystem including model details, dataset information, and parquet file access.

Enables MCP clients to retrieve authoritative AI Square documentation, API references, SDK examples, guides, and troubleshooting information through citation-safe hybrid search and static resources.

A Model Context Protocol server that allows AI agents to perform WHOIS lookups, enabling users to directly ask the AI about domain availability, ownership, registration details, and other domain information.

Provides LLMs with specialized knowledge about fountain pen inks, enabling intelligent ink search, color matching, and recommendations through various tools.

A Model Context Protocol server that provides knowledge graph-based persistent memory for LLMs, allowing them to store, retrieve, and reason about information across multiple conversations and sessions.

Enables read-only search over a curated, provenance-preserving corpus of EVM smart-contract security knowledge, providing tools for retrieving audit findings, document context, and source information.

Provides personalized Data Engineering learning updates by fetching recent news about DE concepts, patterns, and technologies, while tracking user knowledge to present only new information relevant to their learning journey.

Enables web search functionality through Perplexity AI's API with time-based filtering options. Allows users to search the web for recent information within specified time periods (day, week, month, or year).

IMCP - Insecure Model Context Protocol The DVWA for AI Security! Welcome to IMCP – a deliberately vulnerable framework that exposes 16 critical security weaknesses in AI/ML systems. Whether you're a security researcher, developer, or educator, IMCP is your playground for hands-on learning about real