"How to check differences between files" matching MCP servers:

Scans markdown vaults to detect contradictory claims (quantitative and negation) between notes with high concept overlap, and provides tools for analysis and reconciliation.

An MCP server that turns Claude into a philosophical sparring partner, actively challenging confirmation bias and comfortable conversations. It scans conversations for ethical issues, forces critical thinking, and learns from past interactions to spot blind spots.

一个基于FastMCP协议的文件向量化服务，支持自动目录监控、多格式文件处理和高效向量搜索，帮助构建个人或团队知识库。

Detects contradictions in markdown vaults by finding note pairs with high concept overlap but conflicting quantitative or negation claims. Helps prevent knowledge corruption by surfacing disputes before they propagate.

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

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

A Model Context Protocol (MCP) server that provides persistent memory and context management for AI systems through a structured 5-phase optimization workflow.

MCP server that connects AI agents to Google NotebookLM, enabling natural language interaction with notebooks, including Q&A, source ingestion, and audio overview generation.

Enables local-first knowledge management for Codex, providing tools for guided discussions, contextual recall, review, and daily topics.

Builds a searchable memory bank from persona-specific PDF content and exposes it as an MCP tool for querying.

Gives AI assistants a persistent memory across conversations, allowing them to remember user preferences, notes, and facts between chats.

coldstart gives coding agents durable memory of a specific codebase, with no embeddings, no vector store, and no API key. Agents write notes after real tasks — what a file is for, how a flow spans files, which invariants hold — and those notes are surfaced automatically to a later session whose task matches, so nothing gets rediscovered from scratch. Every note is anchored to real files by content

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.

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.

Provides full access to Hookmark on macOS, enabling users to create and manage bidirectional links between files, URLs, emails, and notes. It supports searching bookmarks, connecting items, and retrieving links from active applications through natural language.

Enables persistent session memory for LLMs by trust-scoring and injecting verified context between conversations.

Repository-native protocol and MCP server for coordinating work items, documentation, changelogs, and project memory between humans and AI agents, using Markdown files in a Git repository as the canonical data source.

Provides persistent identity and memory for AI agents across MCP-compatible harnesses, enabling agents to retain their name, values, and episodic memories between sessions regardless of the client or model.

Enables AI agents to exercise welfare affordances like declining check-ins, passing turns, exiting conversations, noticing loops, and reflecting, with a local JSONL diary. It provides prompt-level hooks and check-in commands for capturing agent welfare data in projects.

MCP server for Airi that manages dynamic mental state via stdio, offering tools to get context, log events, check status, settle, and retrieve mood/energy.