"An overview of end-to-end testing" matching MCP servers:

Enables semantic search over local knowledge bases like Obsidian notes, SQLite, and plaintext files, exposing results to Claude via MCP server.

A scientific reasoning framework that leverages graph structures and the Model Context Protocol (MCP) to process complex scientific queries through an Advanced Scientific Reasoning Graph-of-Thoughts (ASR-GoT) approach.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

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.

Turn Obsidian notes into agent-ready context, preview-only plans, and safe repo handoffs.

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.

Enables sophisticated reasoning workflows using graph-based representations for AI models.

Provenance tree for work: every node knows which node it was born from

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.

Enables AI coding agents to retain and recall project context across sessions through local Markdown storage and hybrid keyword/semantic retrieval, including reusable knowledge cards. It runs offline as a daemon and integrates with MCP-compatible IDEs to continue long-running work without re-explaining decisions or architecture.

Enables insurance claims review assistance by querying a knowledge graph of Korean standard insurance terms, restoring applicable policy versions by enrollment date, and returning coverage/exclusion determinations with cited provisions.

This MCP server enables AI agents to manage artifacts across sessions by providing tools for searching, retrieving, and registering entries in a persistent ledger, ensuring consistency and traceability of agent outputs.

Transforms Claude into a persistent intelligence layer with automatic checkpointing, crash recovery, semantic memory, and cross-project learning. It provides 128+ tools for session management, adversarial testing, and browser automation to eliminate state loss and context rebuild costs.

Enables a simulated Alexa+ care companion to capture daily check-ins, recall longitudinal care-journal history, assess risk, create local family-inbox cards, schedule follow-ups, and produce weekly digests through MCP tools.

Enables context capture and reinforcement learning by recording successful work patterns and creating reasoning chains for cross-conversation continuity. Automatically captures positive feedback through Claude Code hooks to build reusable success patterns.

Provides LLMs with access to molt-md, an encrypted markdown document hosting service, for managing and reading secure knowledge bases. It enables users to create, update, and organize encrypted documents into workspaces with full version control and end-to-end encryption.

Enables AI assistants to query end-to-end encrypted memories from Cognia workspace via MCP. Supports search, retrieval, and action execution against connected services like Slack, Notion, and GitHub.

Local end-to-end RAG system for agentic code editors, exposing retrieval-augmented generation via MCP to any compatible client.

Enables Claude to read, search, summarise and post entries in an end-to-end encrypted Pyunto exchange diary, decrypting only on the user's own machine. Users initiate every interaction, pairing by QR code and using tools such as read_thread and post_entry so the diary becomes long-term memory alongside the phone app.

A server that manages conversation context for LLM interactions, storing recent prompts and providing relevant context for each user via REST API endpoints.