Exposes local LM Studio language models as MCP tools, enabling chat completions and model listing through a local OpenAI-compatible API without requiring API keys.
Enables MCP-compatible AI clients to invoke CLI-driven agent tools over Streamable HTTP, including shell execution, file operations, patching, image viewing, web search, and nested agent tasks, with permission modes and real-time progress streaming.
Enables AI assistants to execute Python functions and system commands via Streamable HTTP, including bash, Python code execution, file operations, and text searching.
A modular platform that enables LLM agents to discover, register, and execute both local tools and tools from external MCP servers, with REST APIs for server management and Streamable HTTP support.
Flask-based server that exposes callable tools via HTTP endpoints for AI agents like Gemini CLI, enabling agent orchestration, tool introspection, and workflow automation with a centralized tool registry.