"Running queries in Apache Superset" matching MCP servers:

A Model Context Protocol server that provides seamless access to multiple storage services including S3, Azure Blob Storage, and Google Cloud Storage through Apache OpenDAL™.

An MCP server that exposes a single tool, jq, for running jq filters against JSON files on disk.

An MCP server built with FastMCP that provides basic terminal abilities like running commands, running Python, and working with files and folders.

An MCP server that wraps Apache Tika to extract text, metadata, and more from documents. It supports local files and optional remote URLs with SSRF protections.

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

Enables uploading images to a running PicGo application through its built-in server.

Enables AI agents and development tools to interact with Obsidian vaults via MCP, providing direct filesystem access for reading, writing, searching, and managing notes without requiring Obsidian to be running.

An Obsidian plugin that runs an MCP server, enabling AI agents to read, edit, search notes, and run Dataview queries in your vault.

Provides file system operations (read, search, list) and time queries, enabling Claude to interact with files and get time in any timezone.

A read-only MCP server that reports largest files, folder sizes, and disk usage, running locally without any data leaving your machine.

Provides full read and write access to Excel workbooks (sheets, cell ranges, tables, formulas, formatting, and cross-workbook references) via MCP, running locally or as an HTTP/SSE service.

A local evidence recorder that captures screenshots, recordings, notes, and summaries during long-running agent tasks, enabling reviewable task records with timelines and artifacts.

Enables listing and running Ansible playbooks, managing roles, reading docs, and creating vars files for the jetlag project.

Enables AI clients to read, write, search, and manage files in an Obsidian vault via MCP over SSE, running standalone without the Obsidian desktop app.

Captures screenshots and saves them to file paths specified by client applications, primarily designed to facilitate screenshot analysis by AI assistants running in WSL environments.

Extracts text and metadata from various file formats (PDF, DOCX, images with OCR) using Apache Tika, enabling AI assistants to understand file contents.

Enables AI agents to operate a persistent Linux sandbox in the cloud, running commands, managing files, using Git, and publishing artifacts through a Streamable HTTP MCP endpoint.

Enables AI agents to develop within a local project workspace by reading and modifying files, running commands and tests, checking Git state, and persisting progress as history sessions that can be restored in later conversations.

Enables intelligent file searching in local directories using natural language queries. Supports searching by file type, filename patterns, and content across multiple formats including PDF, Word, Excel, and text files with AI-powered relevance scoring.

Local MCP server enabling ChatGPT to reference large files by path, manage long-running jobs, and register local resources like screenshots and logs without modifying source files.