"Reactive Resume" matching MCP servers:

A local MCP server for low-token co-reading: import a book, split it into chapter-sized chunks, read it chunk by chunk, and keep notes so a session can resume without re-reading the whole book.

Enables managing a job search through natural language: tracking applications, discovery leads, interview prep, and resume generation. Connects to Claude via MCP to read and update local Excel files and documents.

Enables AI agents to query a professional profile in real time through tools for experiences, skills, projects, summary, recommendations, and GitHub repositories. It also serves a bilingual landing page and generated resume PDF from the same profile data.

Enables a shared reading room where users and Claude can import EPUB or text books, read chunk-by-chunk, annotate passages, search, track progress, and resume from unread sections.

Enables AI assistants to query a user's recorded work sessions, notes, and browsing history, allowing them to resume tasks or answer questions about past work without re-explanation.

Lets coding agents like Codex, Cursor, and Claude Code share and resume each other's chats, and attach to a common task with saved notes that can be searched later. This keeps task state and decisions in sync no matter which agent you switch to.

An MCP server that gives Claude and other MCP clients persistent, graph-structured memory by storing it in a self-hosted TriliumNext knowledge base, so sessions resume with context instead of starting from zero.

Enables AI agents to share a local, searchable context store with summary-first reads, so a new agent can resume a long-running task at a flat token cost without re-reading prior history.

Provides AI clients with per-project todo management and persistent context notes via MCP, enabling task tracking and resume summaries.