"author:cbuntingde" matching MCP servers:

Enables agents to maintain persistent memory through three-tiered architecture: short-term session context with TTL, long-term user profiles and preferences, and searchable episodic event history with sentiment analysis. Provides comprehensive memory management for personalized AI interactions.

Enterprise-grade MCP (Model Context Protocol) server for detecting secrets and sensitive information in GitHub repositories. Scans for 35+ types of secrets including API keys, passwords, tokens, and credentials with production-ready reliability features.

An enhanced Model Context Protocol (MCP) server implementing the Ralph Wiggum technique for iterative, self-referential AI development loops.

A stateful MCP server that provides persistent memory, deterministic static analysis, and evolving conventions for AI coding assistants.

Integrates with Google CodeWiki to search, fetch, and cache documentation for GitHub repositories, enabling easy access to repository documentation through natural language queries.

A persistent, project-scoped memory layer for AI coding agents, providing 39 tools for capturing, searching, deduplicating, relating, and maintaining memory records across long-running coding sessions.

An MCP server for intelligent memory and task management with semantic search, automatic task extraction, and knowledge graphs, enabling AI assistants to maintain context and learn project conventions.

Provides a local-first persistent memory layer for coding assistants, enabling cross-project user preferences, per-project durable and working memory, session archives, and reflective recommendations through MCP tools.