A dashboard for running and coordinating multiple AI CLI agents at once.
Powerful AI Client
Salesforce Hosted MCP Servers
Neo4j Labs Model Context Protocol servers
SQL transactions learning tool (AI ready)
This MCP server integrates with your Google Drive and Google Sheets, to enable creating and modifying spreadsheets.
MCP Server for AI automation of the PlayCanvas Editor

Public repository for Advanced Unity MCP by Code Maestro (www.code-maestro.com).
Local MCP server that lets AI assistants automate Origin/OriginPro for data and image processing.
Model Context Protocol (MCP) Server for the Keboola Platform
a coding Agent, rpc plugin, sub-agents, hashline edits, and mcp
🏠 Tells you what changed on your server — only what's worth telling. Single Go binary, no daemon, no database, MCP server built in.

Official Model Studio CLI(阿里云百炼 CLI)built for AI Agent frameworks, exposing models, search, multimodal, and workflow capabilities as structured tool calls.
AI conversations that actually remember. Never re-explain your project to your AI again. Join our Discord: https://discord.gg/tyvKNccgqN
Open-source AI coding agent and agent runtime: one binary, any model, MCP-native. Runs in terminal, CI, or as a daemon.
🧠 The Brain for Your AI — Local-first memory engine for AI agents. Store, recall, and search memories with semantic embeddings. Single Rust binary, zero config, fully offline.
First open-source OpenEvidence MCP server: browser-session medical research tools for Codex, Claude Code, and MCP clients

The security-first skill manager for AI agents — every install runs a security scan. Manage skills & MCP servers across 87 agents. Zero-dependency CLI.
Structural code intelligence for AI agents — semantic search, knowledge graphs, and a built-in MCP server in one Rust binary. Give Claude, Cursor, and any MCP client a deep understanding of your codebase.

Synthadoc: An open-source LLM knowledge compilation engine that turns raw documents into structured, local-first wikis. A transparent, human-readable alternative to traditional RAG, which can be self-managed and self-improved without the use of any tools.
Local-first CLI for agent skills, browser automation, knowledge bases, external CLIs, and terminal AI chat.