"MEGA" matching MCP servers:

Enables AI coding assistants to share persistent local memory across sessions and agents, so rules, mandatory specs, verified code snippets, and past mistakes are automatically surfaced before code is generated. It also lets agents log repeated failures as recurrence-counted 'vaccines', preventing the same errors from recurring across Claude, VS Code agents, and local LLMs.

Hardened MCP bridge to the full Ollama ecosystem — local and cloud models. 6 tools covering health, model management, chat, and generation with SSRF mitigation, singleton HTTP client, and structured error handling. Two deps, one file.

MCP server for the Meta-Consciousness (MCAI) theory: term definitions, concept relations and source citations, served from a local knowledge base.

Transforms complex Pega Platform interactions into intuitive, conversational experiences by exposing Pega DX APIs through the standardized Model Context Protocol, enabling AI applications to interact with Pega through natural language.

A server that transforms a standard Language Model into a dynamic multi-agent system where the model simulates both a Conductor (project manager) and Experts (specialized agents) to tackle complex problems through a collaborative workflow.

Provides a semantic search interface that enables discovery and routing across over 1,000 local MCP tools using natural language queries. It leverages hybrid search and embeddings to accurately match user intent with tool names and descriptions.

A flexible proxy that enables discovery and execution of tools across multiple Model Context Protocol (MCP) servers and JavaScript functions, reducing context size even when dealing with hundreds of tools.

Aggregates multiple remote Model Context Protocol endpoints and exposes them through a unified SSE interface, allowing an LLM client to interact with specialized servers without configuration changes.