"Testing subscribe functionality on a Python server" matching MCP servers:

A simple note-taking MCP server that allows adding notes and summarizing them via a prompt.

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.

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.

A Model Context Protocol server that enables AI agents to query a Graphiti knowledge graph and pgvector document store for evidence-backed responses via hybrid search and RAG.

A sophisticated AI-powered server providing intelligent, context-aware conversational capabilities with role-based advisors, semantic memory, multi-LLM support, and web browsing.

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.

On Board is a local MCP server that gives multiple AI agents and IDEs a shared project memory, ticket queue, and handoff history, so agents can seamlessly continue each other's work. It supports agent-to-agent wake events, enabling autonomous workflows like reject-fix-resubmit cycles without human relay.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

Provides knowledge graph functionality for managing entities, relations, and observations in memory with strict validation rules to maintain data consistency.

A Python-based server providing persistent memory management for AI models with SQLite and Markdown dual backend storage. It features full-text search, RAG-enhanced querying, and cross-project knowledge sharing for integration with Claude, Cursor, and Rovo Dev.

Enables AI agents to maintain persistent, searchable two-layer memory with 37 tools, hybrid search, knowledge graphs, and enterprise features like authentication and backups.

Project management and session memory for AI agents that provides 13 tools for tracking projects, tasks, and context during AI coding sessions.

Enables querying PDF documents using natural language with grounded answers and source citations via a local RAG pipeline.

A server that manages conversation context for LLM interactions, storing recent prompts and providing relevant context for each user via REST API endpoints.

A lightweight MCP server for semantic search over markdown knowledge bases, enabling AI coding agents to index, search, and answer questions from local markdown documents.

MCP server that exposes Open WebUI Knowledge Bases as tools and resources, enabling AI assistants to search and access knowledge bases.

MCP server for integrating LightRAG with AI tools. Provides a unified interface for interacting with LightRAG API through the MCP protocol.

A local-first RAG system that indexes personal documents and enables querying them via an MCP tool, keeping data private with local embeddings.

A FastAPI server that implements the Model Context Protocol (MCP) using Server-Sent Events (SSE) transport to provide random cat facts on demand or as a continuous stream.

Enables AI assistants to persistently add, read, and summarize sticky notes through MCP-compliant tools, resources, and prompts.