"Overview of AWS Services" matching MCP servers:

Enables users to access, search, and get recommendations from AWS documentation through natural language queries. Supports both global AWS documentation and AWS China documentation with tools to fetch pages, search content, and discover related resources.

Self-hosted memo knowledge base with MCP, REST, and read-only web interfaces; lets AI agents save and retrieve tagged, searchable study notes for AWS DevOps Pro exam prep.

An MCP server for managing contextual data as markdown files with metadata, enabling agents to save, retrieve, search, and delete contexts using simple CRUD operations.

Memory vaults on your own machine, one per life domain, retrieved with a local BM25 index fused with vector search, where the human decides which vaults a model may answer from. Requires the Mnemosyne OS desktop app running locally; it also reports what other coding agents on the same machine are doing.

Privacy-first local document search using semantic search. Runs entirely on your machine with no cloud services, supporting PDF, DOCX, TXT, and Markdown files.

Project Memory stores decisions, evidence, outcomes and reviewed lessons in local SQLite. Assistants retrieve bounded context through three MCP tools. People follow and plan work in a live workspace with an overview, sprint board, decision history, readable documents, skills and project maps. Offline exports remain available.

Local-first memory engine for AI-agent teams: private/team/project ACL, associative recall, and federated sync across nodes. One SQLite file, no LLM required.

A redaction engine and MCP server that scrubs sensitive identifiers (AWS keys, IPs, emails, etc.) from AI agent traces, enabling safe storage and sharing of war stories via submit, search, and retrieve tools.

Enables code agents to persist and recall durable project knowledge — rules, decisions, procedures, learnings and secrets — across sessions at low context cost, with accent-insensitive PT-BR search, scoped per repository/workspace, and secrets that stay out of the model's context.

Enables local semantic search and management of OKF knowledge bundles via MCP tools, with hybrid BM25 and vector search.

MCP server for Google NotebookLM enabling notebook, source, and audio overview management with hybrid metadata storage.

A project-agnostic Open Knowledge Format MCP server that indexes Markdown concepts with YAML frontmatter and provides CLI and MCP tools for search, validation, and graph navigation of structured knowledge.

Provides local-first durable memory and session continuity for AI coding agents over MCP, enabling context across restarts without cloud services or telemetry.

AoT MCP server enables AI models to solve complex reasoning problems by decomposing them into independent, reusable atomic units of thought, featuring a powerful decomposition-contraction mechanism that allows for deep exploration of problem spaces while maintaining high confidence in conclusions.

A Model Context Protocol server that provides persistent storage, categorization, and retrieval of bookmarks through AI clients like Claude. It allows users to manage web links using custom categories and includes options for local JSON storage or AWS S3 synchronization.

Provides semantic memory and persistent storage for Claude, leveraging ChromaDB and sentence transformers for enhanced search and retrieval capabilities.

A read-only MCP server that lets AI agents search and retrieve the Wheel of Heaven corpus, including source-grounded facts, interpretations, and comparative traditions, all with full epistemic metadata.

An open-source memory layer that provides persistent project context and architectural history for AI development tools across multiple platforms and sessions. It enables AI assistants to maintain a shared understanding of codebases while integrating directly with services like Notion for documentation management.

File-backed Memory MCP Server for multi-agent coordination, enabling AI coding agents to persistently store and search memories using JSON files without external services.

Provides intelligent, persistent memory for AI assistants with semantic search, natural language queries, and OAuth-based team collaboration, enabling context-aware conversations across multiple clients.