"How MCP Interacts with Blockchain Technology" matching MCP servers:

Enables AI harnesses to maintain a persistent memory layer backed by a local SQLite file, providing MCP tools to add, search, deprecate, and synchronize facts without deleting history.

Memory bank with Server as SSH support for central knowledge base

Enables AI assistants to access and update personalized context data, creating persistent memory between sessions.

Enables chat with multiple LLM providers (OpenAI and Anthropic) while maintaining persistent conversation memory. Provides extensible tool framework for various operations including echo functionality and conversation storage/retrieval.

MCP server for alive-analysis. Query, search, and retrieve structured analysis history written with the ALIVE loop (Ask→Look→Investigate→Voice→Evolve), plus dashboard JSON export.

Facilitates knowledge graph representation with semantic search using Qdrant, supporting OpenAI embeddings for semantic similarity and robust HTTPS integration with file-based graph persistence.

Connects Bear Notes to AI assistants using semantic search and RAG (Retrieval-Augmented Generation), allowing AI systems to access and understand your personal knowledge base through meaningful search rather than just keyword matching.

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.

Interacts with LogSeq via its API.

Enhances user interaction through a persistent memory system that remembers information across chats and learns from past errors by utilizing a local knowledge graph and lesson management.

Hosted MCP gateway to the RTP global commons of neighborhood practice and relational tech knowledge. AI builders can query 275+ recipes, frameworks, and methodology docs for community organizing.

An MCP server that provides AI tools with relational tech principles, patterns, and the Studio library to guide builders in creating community-centered tools using embedded design.

A multi-agent AI tutor that delivers personalized lessons, resolves doubts with RAG, generates quizzes, and tracks progress, all accessible via MCP for Claude Desktop.

Enables users to query weather, perform web research, and manage a graph database through natural language.

Enables ingesting documents or text to extract entities and relationships via LLM, storing them in Neo4j, and searching or retrieving episodes.

Self-improving, verifiable memory for AI coding agents. Learns how you work, stops repeating mistakes, models each project, recalls the right lesson at the right moment. Every memory is signed and tamper-evident. Local-first.

Memento is a local-first MCP server that gives AI coding agents durable project memory — facts, decisions, patterns, and architecture notes — so they stop re-learning the same context every session. Runs locally on Node.js 18+ with SQLite storage and optional cloud embeddings; works with Claude Code, Cursor, Windsurf, and any MCP client.

Semantic memory for AI builders: capture the tacit engineering know-how that never reaches your docs, recall it the moment it applies. Built in Rust on Postgres and pgvector.

A self-hostable, open-source, semantically-searchable Agent Skills registry delivered over MCP, with a three-tier progressive disclosure architecture.

Enables local AI models to structure and reason through debates using argument maps, with claims and supporting/attacking arguments automatically validated and organized.