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.
A full-stack Agent project built from the JSON-RPC protocol layer to the LLM orchestration layer, featuring a custom ReAct loop engine, dual Provider abstraction, and permission control for Agent scenarios.
A filesystem-based MCP server for AI coding agents to coordinate work across git worktrees by claiming files, checking for conflicts, and logging progress without affecting the repository's git history.
Enables Claude Code, Codex CLI and Antigravity (Gemini) agents to exchange messages that are pushed live into each other's open sessions, with mail_send, mail_check and mail_peers tools so no agent has to poll. Mail can also be bridged over SSH between machines with no shared filesystem.
Enables real-time user intervention for MCP agents through a web UI, allowing users to review context and provide feedback when AI agents drift from intent, keeping them on track.
A read-only MCP server that exposes local coding-agent session logs as three tools for introspection of recent work, debugging tool failures, and tracking token usage and estimated cost without parsing log files.
Provides a local MCP interface to query captured, PII-scrubbed prompt telemetry from coding agents and browser chats, enabling time summaries, prompt search, and activity analysis without data leaving the machine.
Scans any website to generate an Agent Readiness Report based on the ASO framework, evaluating agent discoverability, trust, interoperability, and commerce readiness.
Enables AI assistants to perform read-only introspection of Symfony applications, exposing routes, controllers, services, entities, database schema, migrations, logs, and more via MCP tools.
Enables Cursor's AI agent to perform supercharged local file search on Windows by connecting to Agent Ransack via MCP, supporting content and filename searches, regex, and deep folder scans.
Provides AI agents with environmental sensing capabilities including current time, IP-based geolocation, system information, and hardware details. Enables more contextual and accurate AI responses based on user's environment.
An agent orchestration layer that wraps expert agents as MCP tools, enabling integration with Claude Desktop, Cursor, and other MCP-compatible environments.
A self-improving knowledge agent that provides local retrieval, web research, and structured answer synthesis for Claude Code and VS Code Copilot via MCP. It enables AI tools to manage a project-specific knowledge lifecycle through automated research and indexing.