"Firebase: Google's Backend-as-a-Service Platform" matching MCP servers:

A local, read-only MCP server that analyzes Python backend projects by providing tools to scan, map, and selectively read files, reducing token usage for AI clients.

Enables comprehensive filesystem operations across Linux, macOS, and Windows with platform-aware command execution, secure path restrictions, and intelligent adaptations for file search, directory management, and shell commands specific to each operating system.

Enables AI agents to remotely operate visual design tools via MCP protocol, with composable architecture for image processing, file operations, and workflow automation.

Lets any MCP-compatible AI assistant read and edit Autodesk Civil 3D drawings through tools for alignments, surfaces, corridors, pipe networks, quantity takeoff, and cut/fill, using a local bridge plugin and named pipes.

A FastAPI-based JSON-RPC 2.0 server implementation that enables users to work with HDF5 files, submit Slurm jobs, retrieve CPU information, and visualize CSV data through standardized API endpoints.

Enables AI agents to interact with both frontend and backend projects by providing file system access and context through the MCP protocol, facilitating full-stack development assistance.

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.

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.

A self-hosted MCP server that enables AI coding agents to read, edit, search, and run code in local projects with human review loops and policy controls.

Enables interaction with the WhkerDB shared PDF editor to manage collaborative rooms, file structures, and real-time annotations. It allows users to upload PDFs and images, manage note trees, and sync data across platforms through natural language.

Provides a secure workspace for AI-driven file management and Python script execution designed to run on Vercel. It enables tools for full file operations and code execution within a sandboxed environment.

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.

A local stdio MCP server for generating images using Google's Gemini image models, saving to disk as JPEG.

locidx

Enables AI assistants to deploy static websites to the Demox platform with automatic directory packaging and cloud storage integration. It includes tools for managing deployments, such as listing, viewing, and deleting websites.

A comprehensive MCP tools collection providing filesystem operations, command execution, system tools, and more, with cross-platform support and strong security features.

Provides unified access to multiple file systems (local, S3, WebDAV, etc.) through OpenDAL, enabling file operations and cross-backend management.

Gives AI assistants full control over a VPS via SSH, enabling command execution, file management, service control, Docker and firewall management.

Enables MCP clients to run OCR on local image files through a single long-lived PaddleOCR backend shared across clients, returning recognized lines as a Markdown table with optional coordinate and confidence columns.

An MCP server that enables users to download webpages as markdown files using r.jina.ai service, with features for configurable download directories and automatic date-stamped filenames.