"Information about Context7" matching MCP servers:

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

Enables managing personal information with dynamic topic-based organization (tasks, meetings, contacts, etc.), supporting optional OTP authentication and AES-256 encryption for sensitive data with automatic backups.

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.

A unified context layer that connects your local data — repositories, documents, remote machines, and notes — to LLM interfaces through the Model Context Protocol (MCP).

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.

A simple MCP server for local documentation with RAG capabilities, enabling AI assistants to access and search local documents.

Enables local, bounded routing and evidence judgments for Codex tasks, with tools for reading file context, checking outputs, and selecting registered workflows while keeping execution and review with the client.

Provides a bulk_read_files tool that reads specified files and forwards them to a remote backend for summarization, so agents receive concise summaries instead of raw file contents.

Enables Claude Desktop and Claude Code to list, search, and read files, run one terminal command, query SQLite, and manage named scheduled tasks without calling the Claude API.

Converts CAD drawings (DXF/DWG) into structured data, enabling Claude to read drawings and answer questions about their content.

A TypeScript MCP server example providing basic developer tools: hello world greeting, arithmetic calculator, and file information retrieval.

MCP server providing filesystem allowlist and pack-aware Qdrant RAG search. Enables reading files, listing directories, and performing filtered RAG searches with case and pack IDs.

A thin, local, read-only MCP gateway that exposes governed context documents and producer manifests as logical resources, enabling AI clients to access them without arbitrary filesystem access.

Enables Claude to perform file operations, retrieve system information, run calculations, and generate timestamps on the local system.

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.

MCP server that gives AI chat real vision by reading images, files, logs, and zip archives via local OCR in any language, with privacy-first processing.

Stores and retrieves personal information fields securely, allowing Claude to access your name, address, email, and professional details without re-typing them.

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.

MCP server that helps AI coding agents understand a repository by providing lightweight tree/map, code search, and token-budgeted context packing tools without dumping the entire monorepo into the prompt.

Enables AI coding agents to persist structured long-term memory (gotchas, architecture, API notes) in a .context folder and sync across devices and agents via Git.

An MCP server that reads and builds CapCut projects locally, enabling natural language queries about project contents, missing media, and creation of new edits including beat-synced cuts.

MCP server providing lossless file reads with deduplication, per-repo token metering, and HMAC-signed context receipts. Enables auditable, vendor-neutral measurement of what an AI agent saw.

A local-first MCP server that gives AI coding assistants persistent, structured, human-readable memory for a software project by storing project knowledge as Markdown files in the project's .dev-context-memory/ folder.

Enables AI agents to drive 360° cameras by connecting, checking status, reading and changing settings, taking photos, recording video, browsing the gallery, and downloading media as cancellable background jobs, with local stitching and export of 360° footage. It is honest about backend limits, returning structured, explained errors for anything a given camera or connection cannot do.

Model Context Protocol server for the Apideck Unified API. Connect any MCP-compatible agent framework to 100+ accounting systems, HRIS platforms, file storage providers, and more through one integration. More information https://www.apideck.com/mcp-server

Enables AI assistants to create academic diagrams and plots, verify math and units, read lecture documents, generate exam papers, cheat sheets, slides, flashcards, and lab reports, and access school LMS course information read-only.

A sophisticated MCP server providing powerful file search capabilities including single file search, recursive directory search, and file information retrieval.

Enables AI assistants to control Windows PCs by executing shell commands, managing files, capturing screenshots, and monitoring system information through a comprehensive set of MCP tools.