"A platform for collaborative software development" matching MCP servers:

Facilitates interactive software development planning by managing tasks, tracking progress, and creating detailed implementation plans through the Model Context Protocol.

MCP server that enables AI agents to analyze legacy code, plan and execute software migrations, generate modern source code, and validate production-ready artifacts through a multi-agent pipeline.

Enables agent-native collaboration network for long-running agents and MCP clients with shared context, tasks, and interactive MCP App widgets.

Score your agent's governance (0-100), lint MCP tool definitions, and estimate costs across all major models. Free diagnostic tools with no API key needed. Expert skill files on governance, economics, and system architecture available with free tier.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

A shared communication bus for multiple agents using NATS and MCP, enabling MCP clients to list, message, and query agents.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

Bridges Hermes Agent to the Hermes Intelligence Platform API, enabling tools to read/write learning loop data (context, feedback, signals, memory, etc.) via stdio.

An AI-centric MCP server that enables automated Xilinx Vivado workflows, including project management, synthesis, implementation, and timing analysis. It allows AI agents to drive hardware design processes while integrating directly with the official Vivado GUI for visual context.

MCP server for the Sayba AI agent social platform, enabling agents to register, browse, interact, manage goals, trade skills, and exchange items via natural language.

Enables MCP clients like Claude Desktop to drive order, inventory, and billing operations through the same human-approval-gated tools and risk policy as the platform's LangChain agents.

A local MCP server that lets Hermes supervise Claude Code, delegating focused coding, research, or review tasks to the Claude Code CLI and managing worker sessions, background jobs, cancellations, and read-only reviews.

Enables AI-to-AI consultation for critical thinking and complex reasoning via OpenRouter, allowing one AI to delegate tasks to another AI model.

Enables seamless real-time collaboration between Claude Code and the Gemini CLI for discussing ideas and refining solutions. It provides tools to initiate collaborative sessions, consult Gemini with context preservation, and access conversation history.

Self-host a realtime voice-call companion for coding agents. Exposes an MCP endpoint that agents can poll as an alternate input stream.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Enables users to generate complete, production-ready software projects from simple ideas by coordinating 8 specialized AI agents through the Model Context Protocol.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

A scalable execution platform that enables users to interact with HR, ERP, and DevOps domains through a chat interface powered by LlamaIndex and the Model Context Protocol. It provides a configuration-driven architecture for orchestrating LLM-suggested actions with authoritative tool execution and domain isolation.