"Techniques for Enhancing Memory and Augmenting Cognitive Thinking" matching MCP servers:

Simple sequential thinking MCP in python

Forces host coding agents through a structured multi-step reasoning protocol, scaffolding, validating, and formatting their thinking in QUICK, STANDARD, or DEEP modes, plus independent refutation and self-consistency verification passes. It runs entirely locally over stdio or Streamable HTTP using bash with no LLM, API key, GPU, or inference cost.

MCP server for structured reasoning with cognitive trap detection, verification, and context compression

An advanced MCP server implementing diagrammatic reasoning with memory-augmented spatial exploration, enabling structured chain-of-thought reasoning through visual reasoning spaces.

An advanced MCP server that implements sophisticated sequential thinking using a coordinated team of specialized AI agents (Planner, Researcher, Analyzer, Critic, Synthesizer) to deeply analyze problems and provide high-quality, structured reasoning.

MCP server providing persistent memory for AI applications, enabling Claude to store and recall memories with hybrid search and knowledge graph.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

Provides persistent memory for AI agents using hybrid search (vector embeddings + BM25) with neural reranking, enabling storage and retrieval of insights, debugging solutions, and patterns across coding sessions.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Persistent knowledge graph MCP server with SQLite backend, offering graph traversal, fuzzy search, and temporal queries for entities and relations. It serves as a drop-in replacement for the npm mcp-server-memory with enhanced capabilities.

Enables agents to manage persistent long-term memory through MCP tools for searching, adding, updating, giving feedback, and forgetting memories, with automated pipelines for redaction, distillation, and reconciliation.

A zero-dependency, file-based persistent memory system for AI agents with tiered memory, Ebbinghaus decay, and keyword retrieval.

An MCP server providing long-term memory for LLMs via hybrid search (FTS5 + vector) stored in SQLite, with time-decay scoring and support for multiple AI assistants.

MARM MCP provides persistent memory and structured session context beneath any AI tool, so your agents learn, remember, and collaborate across all your workflows.

Local-first persistent memory layer for MCP agents with hybrid search, file ingestion, and GDPR compliance.

Persistent memory and payment safety for AI agents on Lightning. Enables agents to remember purchases, track vendor reputations, enforce budgets, and share trust signals via Nostr.

Provides persistent memory for Claude with hierarchical categorization, cross-corpus recall, session journals, and customizable persona, enabling memory continuity across sessions.

Two-layer memory for AI agents. Episodes compress into identity. The only MCP memory server with an immune system. Patterns earn permanence through evidence, false knowledge gets caught and demoted, and stale information fades — so your agent's memory gets smarter over time, not just bigger. Zero dependencies. 5 tools. Works with any MCP client.

MCP server for knowledge graphs designed around neurodivergent thinking patterns, organizing memories into five districts with BM25 ranking and bidirectional connections.

MCP server for persistent, cross-session, local-first memory for AI agents, storing memories as Markdown files with SQLite indexing for hybrid search.