"Collaboration Between Multiple AIs via MCP (Master Control Program)" matching MCP servers:

Enables read, write, edit, and file transfer operations on TorchV AIS enterprise knowledge bases. Supports document management, repository browsing, and administrative tasks with configurable readonly, write, or admin permission levels.

Enables collaboration with multiple AI providers (Claude, GPT-4, Gemini, Ollama) directly from VS Code with automatic project context injection and persistent conversation history. Provides streamlined tools for getting AI advice, multi-provider research, and enhanced context sharing across sessions.

A central knowledge hub that connects AI tools to a unified 'Master Brain' with automated memory capabilities. It utilizes intelligent analysis to automatically capture and store key decisions, fixes, and learnings across various development environments.

Enables managing and controlling AnythingLLM instances through MCP, providing tools to list, create, and delete workspaces, retrieve system environment settings, and get vector counts.

An MCP server that enables multi-provider AI collaboration using models like DeepSeek, OpenAI, and Anthropic through strategies such as parallel execution and consensus building. It provides specialized tools for side-by-side content comparison, quality review, and iterative refinement across different AI providers.

Provides semantic search, note retrieval, source explanation, daily digests, and health checks for a local Obsidian vault, enabling MCP clients like Claude Desktop and Claude Code to query the second brain via natural language.

A modular MCP server suite that provides core tools, long-term memory, knowledge RAG, skills registry, and external integrations for AI agents.

A lightweight framework for building and orchestrating AI agents through the Model Context Protocol, enabling users to create scalable multi-agent systems using only configuration files.

A governed MCP server that enforces OAuth 2.1 scope checking and policy-driven access control for AI agents, providing a full audit trail on every tool call. It includes tools for Cisco Webex Contact Center knowledge search and SD-WAN network operations.

160 tools that do that heavy lifting - storage, agent-to-agent collaboration, document conversions, identity verification -- almost all priced under a tenth of a cent or less per call.

Provides a local-first, provenance-aware memory layer that enables MCP-capable AIs to store, recall, validate, and reason over facts with contradiction detection, trust weighting, deduplication, and encryption, supporting offline private operation without GPUs or API keys.

Enables persistent session memory for LLMs by trust-scoring and injecting verified context between conversations.

Enables seamless integration between Ollama's local LLM models and MCP-compatible applications, supporting model management and chat interactions.

An MCP server providing machine translation capabilities via the Lara Translate API, featuring language detection and context-aware translations between numerous language pairs.

A server that enables LLMs like Claude to interact with Azure Cosmos DB databases through natural language queries, acting as a translator between AI assistants and database systems.

Enables AI assistants to intelligently select and switch between different AI models (OpenAI, Anthropic, etc.) within the same conversation based on task requirements. Provides a unified interface for accessing multiple AI providers through a single MCP tool.

A multi-API key load balancing MCP server for Tavily that automatically rotates between multiple API keys to provide high availability and increased request limits.

Arbor is a local-first, high-performance developer tool designed to bridge the gap between static code analysis and AI-driven development.

Provides AI assistants with a local knowledge base and research library, enabling semantic and full-text retrieval, memory persistence, and multi-agent collaboration via 58 MCP tools.

An AI router that connects applications to multiple LLM providers (OpenAI, Anthropic, Google, DeepSeek, Ollama, etc.) with smart model orchestration capabilities, enabling dynamic switching between models for different reasoning tasks.