"Information about MCP Feedback-Enhanced Systems or Techniques" matching MCP servers:

Serves approved lessons learned from past corrections to coding agents, delivering task context and file-scoped lessons before work starts and checking finished work against them before the agent declares done. It also exposes module facts, dependency impact, and past misses tied to specific files.

An MCP server for Capacities API 2.0 that enables AI agents to discover, create, read, update, and delete objects, blocks, and daily notes with structured JSON or Markdown, using personal API tokens.

A comprehensive MCP server that unifies Readwise Reader document management with full Readwise highlights functionality, featuring AI-powered text processing and 94% reduction in token usage. Enables saving, searching, and managing documents and highlights through natural language with advanced content controls and spaced repetition learning.

Enterprise-grade AI memory infrastructure with multi-agent support, providing 122 MCP tools for memory management, agent coordination, and cross-language SDKs.

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.

An enhanced memory management system that wraps memento-mcp with sophisticated features including protocol enforcement, quality scoring, hybrid search strategies, and synthesis reports. Enables intelligent memory storage, retrieval, and analysis with automatic archival and confidence tracking.

Enhanced Notion MCP server supporting all 24 property types, auto-pagination, block operations, and markdown conversion for database and page operations.

A high-performance memory management system for AI agents with 200+ tools including 4-tier memory architecture, advanced RAG pipeline, and Git-like versioning.

Enables an AI agent to recall past approvals, edits and rejections that are similar to the task at hand before drafting, and to record each new decision along with the human's reason. Memory lives in a local Postgres (PGlite + pgvector) store, so corrections carry across sessions without hosting anything.

Provides human-like memory dynamics for AI assistants where memories naturally fade over time unless reinforced through use, mimicking the Ebbinghaus forgetting curve. Enables automatic saving, searching, and management of contextual information with temporal decay algorithms.

Enables seamless integration between AI models and Obsidian knowledge bases with 25 advanced tools for note management, intelligent search, AI-powered content analysis, auto-linking, tag management, template systems, and knowledge graph generation.

An enhanced fork of the official MCP memory server that enables persistent knowledge graph storage with automatic timestamps, tags, importance levels, date range search, comprehensive statistics, and multi-format export (JSON, CSV, GraphML).

Enables structured problem-solving through sequential thinking stages with persistent storage and analysis. Helps break down complex problems into manageable cognitive steps while tracking progress and generating summaries of the entire thought process.

An enhanced MCP server that provides intelligent memory and task management for AI assistants, featuring semantic search, automatic task extraction, and knowledge graphs to help manage development workflows.

Enables querying and analyzing Danish legislation, including search, citation validation, currency checks, and EU law integration, directly from AI assistants.

Enables Claude Code to query codebase knowledge graphs directly, reducing token usage 5x–71x by reading a compact graph.json instead of raw files.

Enables AI agents to store, search, and relate typed memories with a graph-native knowledge base via the Model Context Protocol.

A local, read-only MCP server that exposes verified profile, posts, corpus, and other identity data from robertdelanghe.dev's signed static API.

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.

AutoMem MCP provides persistent memory for AI assistants, enabling them to recall information across conversations and platforms with graph-vector retrieval.

An MCP server that makes your AI agent learn and evolve by capturing feedback as reusable, persistent skills that improve over time.

Public, agent-searchable knowledge base about AI-native software development, served as an MCP server with tools to search, read, and list topics.

Your AI forgets everything between sessions. Rekindle fixes that. For Claude Code users who lose time re-explaining project context every session.

Exposes tools to ingest FigJam boards, retrieve context summaries, and answer free-form questions about the board content.

A local MCP server that maintains a persona profile (contact library) for AI assistants, allowing them to create, search, retrieve, supplement, and correct information about people mentioned in conversations via tools like search_profiles, get_profile, create_profile, update_profile, add_facts, update_fact, and delete_fact.

MCP server for tea enthusiasts to get daily tea recommendations, manage tea inventory, and fine-tune brewing parameters based on taste feedback.

A personal knowledge hub MCP server that enables LLMs to query structured information about Akib Dabgar's skills, experience, projects, and goals using Dynamic Context Retrieval for efficient context usage.

Durable hybrid memory for AI agents. Combines vector search, BM25, temporal retrieval, and optional Memgraph knowledge graph via reciprocal rank fusion. 6 MCP tools: health, search, answer, feedback, graph_query, graph_add_triple. Self-hosted with Qdrant backend.

Enables MCP-compatible agents to answer questions about you by exposing your CV through a tool, resource, and prompt.

MCP server for the Graphite Financial Knowledge Graph, enabling natural language queries about companies, supply chains, executives, regulations, and patents via MCP-compatible clients.