A production-grade MCP server providing a persistent Python REPL with multi-session support, sandboxing, and timeout protection, enabling LLM agents to execute Python code across multiple turns with variables that persist between calls.
Enables Codex to manage a local Claude Code companion through MCP, implementing a dual-agent workflow where Codex handles reasoning and review while Claude Code performs engineering tasks.
A comprehensive MCP implementation designed for fullstack development that enables code manipulation, terminal command execution, and system notifications. It provides an intelligent agent interface powered by Gemini to automate Python and Next.js development workflows.
Enables AI assistants to securely interact with IBM i (AS/400) systems via ODBC, supporting SQL queries, CL commands, source code reading, compilation, and spoolfile analysis.
Provides AI coding assistants with context optimization tools including targeted file analysis, intelligent terminal command execution with LLM-powered output extraction, and web research capabilities. Helps reduce token usage by extracting only relevant information instead of processing entire files and command outputs.
Provides interactive Python REPL capabilities with persistent sessions, virtual environment support, package management via uv, and development tools like testing, linting, and code formatting for Python projects.
This is a secure Python code execution server that enables LLMs to run Python code safely in isolated Docker containers, supporting stdout capture and Matplotlib PNG generation.
A Python-based MCP server demonstrating basic math and text tools, supporting both SSE and STDIO transports for integration with AI assistants like Cline in VS Code.
A server that manages conversation context for LLM interactions, storing recent prompts and providing relevant context for each user via REST API endpoints.
Enables AI agents to efficiently manage and monitor background processes, with features like process startup, termination, log retrieval, and resource management.
Enables AI clients to securely execute remote commands and transfer files over SSH through standardized MCP tools, with multi-host management, flexible authentication, and an admin console.
Enables AI agents to control Android devices through natural language, supporting app management, UI interaction, gestures, and system operations via uiautomator2.
A lightweight service that enables AI assistants to execute AWS CLI commands through the Model Context Protocol (MCP), allowing AI tools to retrieve AWS documentation and interact with AWS services.
Combines KC Chat Panel session interaction with AgentDock computer control tools, enabling Cursor Cloud Agent to chat and operate the local machine via AgentDock.
Connects AI assistants to a Kali Linux terminal for executing security tools, managing interactive shell sessions, and performing penetration testing, CTF challenges, and security research tasks.