"Information about Context7" matching MCP servers:

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.

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.

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

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 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.

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

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.

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.

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.

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

A modular Python MCP server providing tools for text echoing, system information, time queries, arithmetic, file reading, and more, designed for seamless integration with Cline and other MCP clients.