"Information on Penetration Testing (Pentest)" matching MCP servers:

Enables agents to store, search, and manage a personal penetration testing knowledge base via MCP, using BM25-ranked retrieval with Chinese tokenization, plus draft approval, deduplication, and sensitive-data redaction workflows.

A comprehensive Model Context Protocol (MCP) server implementing the latest MCP specification with tools, resources, prompts, and enhanced sampling capabilities that features HackerNews and GitHub API integrations for AI-powered analysis.

MCP server that provides secure access to a serverless Markdown wiki on AWS, enabling AI assistants to read, search, and edit pages with space-level permission checks and Bedrock-powered semantic search.

This read-only MCP Server allows you to connect to Act-On data from Claude Desktop through CData JDBC Drivers. Free (beta) read/write servers available at https://www.cdata.com/solutions/mcp

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

A Model Context Protocol server that runs on Cloudflare Workers with OAuth login, allowing clients like Claude Desktop to connect to it for tool-augmented AI interactions.

A server for hosting Model Context Protocol (MCP) tools on Cloudflare Workers with OAuth authentication, allowing Claude AI and other MCP clients to access extended capabilities.

A server implementation for the Model Context Protocol (MCP) that runs on Cloudflare Workers and supports OAuth login, allowing Claude AI to use custom tools through local or remote connections.

Deploys a remote MCP server on Cloudflare Workers with AutoRAG capabilities, enabling tools like math operations and RAG-based queries through SSE transport and OAuth authentication.

A Model Context Protocol server that runs on Cloudflare Workers, enabling tools integration with Claude AI through OAuth login.

This MCP server enables any MCP client to perform web searches over HTTP using just an endpoint URL and API key, abstracting away AWS SigV4 signing and Bedrock AgentCore protocol translation entirely server-side.

DevsContext is an MCP server that provides AI coding agents with synthesized engineering context—requirements, decisions, architecture, and standards—from tools like Jira and Slack. It fetches and synthesizes relevant information on demand to help agents work on tasks correctly.

Provides persistent, searchable memory for AI agents, enabling them to retain, recall, and reflect on information across conversations.

A remote MCP server providing a tool for searching and querying ATprotocol documentation, helping developers easily access information while building on the protocol.

An MCP server that provides semantic memory on top of Qdrant vector search, with tools to store and retrieve information using embeddings.

Utilizes Gemini API and Google Search to generate answers based on the latest information for user queries.

Enables AI agents to query a curated, cited knowledge graph on testing, benchmarking, and auditing autonomous agents, returning claims with sources, confidence values, and evidence tiers through eight read-only tools over a remote streamable-HTTP endpoint with no authentication required.

Enables MCP clients to remember user information, preferences, and behaviors across conversations using vector search technology. Built on Cloudflare infrastructure with persistent storage and semantic similarity matching.

MCP Memory is an MCP Server that gives MCP Clients the ability to remember information about users across conversations. It uses vector search technology to find relevant memories based on meaning, not just keywords.

Enables AI assistants to remember user information and preferences across conversations using vector search technology. Built on Cloudflare infrastructure with isolated user namespaces for secure, persistent memory storage.