"The most widely used models" matching MCP servers:

The most feature-complete MCP server for Obsidian vaults. 23 tools and 3 resources for search, read, write, tags, link analysis, graph traversal, and canvas support.

Provides secure filesystem access for AI models through the Model Context Protocol with strict path validation, file operations, directory management, and system command execution within predefined directories.

The Modes MCP Server allows for comprehensive management and control over custom operational modes, supporting full CRUD operations, schema validation, and real-time configuration changes for enhanced mode management.

Implements the Model Context Protocol (MCP) to provide AI models with a standardized interface for connecting to external data sources and tools like file systems, databases, or APIs.

Provides tools for file system operations and text generation using OpenAI-compatible models via the Model Context Protocol, supporting both stdio and HTTP transports.

An MCP server providing direct programmatic access to Obsidian vaults through CouchDB, the database used by Obsidian LiveSync. It enables AI agents to read, write, and manage notes and metadata in headless environments without requiring the Obsidian desktop app.

An HTTP MCP server that indexes large documents into exact-line-numbered sections, enabling AI models to locate, read, summarize, and edit parts of a document without ingesting the whole file.

MCP server for the Solid protocol enabling AI models to read, write, search, and manage resources in Solid pods.

The fastest, most capable filesystem MCP server built in Rust, giving AI agents superpowers to read, search, edit, and manage files and directories.

Enables AI models to search the web using DuckDuckGo, scrape webpage content in markdown format, and browse/read local files for code analysis and debugging.

Analyzes file access times, duplicates, and sizes to identify rarely used files and suggest cleanup for folder restructuring.

MCP server for reading and listing JSON documents, designed to be used with Claude Haiku and Headroom compression to reduce token usage. It demonstrates an end-to-end MCP tool-use loop with stdio transport.

A multi-tool task agent MCP server with file search, SQLite query, calculator, and report writing tools. Enables Claude Code, Claude Desktop, or Cursor to control the same tools used by the agent, with guardrails for safety.

Enables file system operations (read, write, list, search, watch, batch process) via MCP over JSON-RPC 2.0, used by a resume matching agent.

A tutorial MCP server for learning the Model Context Protocol by building file and system tools. Provides hands-on experience creating custom tools that enable AI models to interact with files and execute system commands.

This server provides an API to query Large Language Models using context from local files, supporting various models and file types for context-aware responses.

Enables AI assistants to inspect, create, and report on IFC/BIM files locally, and to open models in a viewer with BCF viewpoint support.

Enables read-only scanning and text extraction from PDF, DOCX, PPTX, SVG, and PNG files in a local folder, providing the raw text to AI models for summarization or analysis without an external LLM API.

A plain-files brain template and MCP server that lets models read owned, portable working memory via list, read, and grep-style search tools.

Token-efficient skim-then-expand I/O for agentic models, enabling lossless reading of large files via skeletons and exact expansion with anchor IDs.