"Secure Shell (SSH) Overview and Usage" matching MCP servers:

Monitors your Cursor usage and provides a conserve flag to the agent, helping you manage request quota by batching questions, preferring defaults, and cutting unnecessary confirmations.

Enables AI agents to manage SSH environments, run remote commands, transfer files, and diagnose connectivity issues for secure server automation.

A tool for detecting and cleaning Java memory shells via local or SSH remote execution. It enables AI agents to scan Java processes, analyze suspicious class code, and safely remove memory shells after user confirmation.

Enables AI assistants to execute shell commands and manage long-running processes within persistent tmux sessions across isolated workspaces. It features a dual-window architecture to separate raw command execution from interactive terminal output.

A server that uses the Model Context Protocol (MCP) to allow AI agents to safely execute shell commands on a host system.

MCP server for agent-native secrets management that stores encrypted secrets with AES-256-GCM, issues short-lived scoped tokens, and injects secrets into requests server-side so agents never handle plaintext credentials.

Enables secure multi-agent property operations with delegated authorization, human approvals, and MCP tool execution through Ruhusa policy enforcement.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Takes a plain-language automation goal and returns a recommended tool stack, command, validation checks, recovery guidance, and a machine-readable package contract for agents and builders.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

MCP server for step-by-step mathematical reasoning and planning, enabling AI agents to execute calculations and perform GUI actions like opening PowerPoint.

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

A Node.js MCP server that wraps the Claude Code CLI to enable parallel execution of AI requests for code generation, editing, and refactoring. It features built-in retry logic, model selection, and JSON validation for structured outputs.

Exposes a synthetic issue tracker and pipeline warehouse as callable tools so an agent can answer operational questions about tickets, pipeline health, runs, incidents, and governed metrics with every claim cited to the exact tool call it came from. All writes are proposal-only, requiring human approval through a gated apply path that logs each step for audit.

An MCP-based trivia game server where AI creates rounds with two true statements and one false 'twist' about various topics, letting players guess which statement is false.

A simple server that acts as a Master Control Program (MCP) for unified interaction with OpenAI and Anthropic (Claude) AI models through a single API endpoint.

A template for creating secure, remotely accessible MCP servers with OAuth authentication and Cloudflare ZeroTrust Access protection. Enables deployment of containerized MCP servers that can be safely accessed by Claude Desktop and other MCP clients through authenticated connections.

TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.

Enables MCP agents to play chess locally, supporting join, state, legal moves, and move execution with per-session color ownership.