"Information about Angular framework or concept" matching MCP servers:

A lightweight and modular framework for building MCP-based file management systems with standardized module structure, flexible configuration, and extensible functionality registration mechanisms.

A general-purpose MCP server that provides utility tools for echo, date/time, and file operations within Claude Code and Claude Desktop. It functions as an extensible framework designed to help developers easily build and register custom Python-based tools.

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.

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.

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Enables storing durable AI memories linked to local JSON or text sources, automatically superseding outdated structured values, flagging ambiguous changes for review, excluding expired information, and preserving revision history in a local SQLite database.

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.

A proof-of-concept MCP server demonstrating various capabilities including mathematical calculations, URL fetching, system information retrieval, data processing, and file operations.

A modular framework for building and running multiple MCP servers with file operations, system information, and extensible tool/prompt/resource support.

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.

A persistent SQLite-backed storage server that enables Cursor IDE's AI assistant to remember information across sessions with global or project-specific scopes. It supports complete CRUD operations, tag-based organization, and keyword search to manage user preferences and context effectively.

A proof-of-concept MCP server that enables reading local files and performing basic arithmetic operations. It provides a simple foundation for understanding how tools are exposed to MCP clients.

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.

Connects AI assistants and IDEs such as Claude Desktop, Claude Code, Cursor, Windsurf and Codex to a local long-term memory store of plain-text .dai files on disk. Enables saving and recalling conversation history through the save_memory and recall_memory tools, with the store readable by any model, editor, or grep and using about a tenth of the tokens.

A proof-of-concept MCP server for AI assistant note-taking, enabling adding notes, fetching the latest note, and summarizing all notes.

A proof-of-concept MCP server that enables LLMs to read local text files and fetch real-time weather data through external tools.

An MCP server for GitHub Copilot that enables reading and processing Excel workbooks (.xlsx) via Docker Compose. Users can extract data from entire workbooks or specific sheets by name or index, returning the information in JSON format.

An MCP server for local PDF inspection that classifies, searches, extracts text and tables without uploading documents or relying on OCR, surfacing reliability warnings for garbled or scanned content.

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

MCP server for lossless YAML 1.2 editing by AI agents. Two tools — noyalib_get (read a value at a dotted/indexed path) and noyalib_set (write a value, preserving comments/formatting byte-for-byte). Pure Rust, streaming-first serde, JSON Schema validation. MIT OR Apache-2.0.

An MCP server for precise, hash-referenced file editing that enables atomic edits using line:hash references instead of fragile line numbers or full content reproduction.

MCP server for AI-powered resume optimization and generation. It enables clients to optimize existing resumes or generate new ones from background info via LLM, producing formatted .docx and .pdf files.