"Information about sequential thinking or related topics" matching MCP servers:

Provides tools to monitor host system health including CPU load, disk usage, and network status while enabling file system management tasks like searching and moving files. It includes built-in safety guards to prevent operations on critical system directories.

A minimal server that provides Claude AI with secure file system access and sequential thinking capabilities, allowing Claude to navigate directories, read files, and break down complex problems into structured thinking steps.

Enables users to ask natural-language questions about a local folder's contents, including file names, sizes, and timestamps, with rollups by type and age and cleanup suggestions for stale or large files. It returns metadata only and cannot read, move, or delete files.

Reads and searches local email archives (.mbox or .eml) with full MIME parsing, enabling queries about senders, subjects, dates, and bodies while keeping all data on your machine.

Searches and browses local Claude Code and Cowork session histories stored on your machine, enabling questions about past work without uploading data.

MCP server that exposes agent-memory-daemon to any MCP-compatible client — Kiro (CLI & IDE), Claude Desktop, Cursor, and others. The daemon does the thinking (consolidation + extraction); this server is a thin filesystem bridge so agents can read, append, and search memory through the Model Context Protocol.

Enables users to access local files, manage persistent notes via CRUD, fetch URLs, inspect system information, and analyze or transform text through MCP tools.

Runs as an MCP server providing file system operations, shell execution, and system information tools, allowing Claude or any MCP client to edit files and control the machine.

Enables saving AI conversation histories as clean, organized markdown notes with automatic filtering of thinking processes and tool execution details, timestamping, and customizable conversation turn limits.

Enables AI coding agents to audit and sweep away transient scratch directories, bloated test caches, and forgotten probe scripts in a workspace, with dry-run previews to guarantee nothing tracked or production-related is touched. It also detects zombie background dev servers still holding common ports like 3000, 5173, and 8000.

mcp using PyPDF2 to: • merge-pdfs • extract-pages • search-pdfs • merge-pdfs-ordered (merge in user spec. order) • find-related-pdfs (regex extracted text for related PDF files)

Enables storing durable AI memories linked to local JSON or text sources, automatically superseding outdated structured values, flagging ambiguous changes for review, excluding expired information, and preserving revision history in a local SQLite database.

Enables triage, installation validation, and controlled automation of X-Ways Forensics and related tools through structured MCP tools for agents.

A read-only MCP server that lets local AI agents inspect open Mac windows, browser tabs, PDFs, clipboard contents, Finder selections, and Messages history so they can answer questions about what the user is currently viewing.

Enables Claude to read and analyze project schedule files in OmniPlan (.oplx) and Microsoft Project (.mpp) formats, answering questions about tasks, milestones, resources, and progress.

MCP server that allows AI agents to read, search, summarize, and answer questions about local PDF, DOCX, XLSX, and TXT files through five tools.

Enables natural-language queries about disk usage by driving WizTree scans and analyzing cached CSV snapshots. Users can find large files, duplicate data, folder breakdowns, and more without repeatedly rescanning the disk.

Enables users to read Moodle course information, list courses, outlines, resources, assignments, and deadlines, and download or extract text from course files locally via an MCP-compatible client.

Enables web AI agents to operate local projects through MCP, with real-time display of the actual model name and thinking effort.

A straightforward task management system enabling sequential task tracking, completion, and progress management through simple function calls or natural language commands.