"MCP Full Stack MVP Development Resources" matching MCP servers:

MCP server that parses 3GPP .docx specifications into structured sections with full-text search, letting LLMs browse, search, and follow cross-references without a vector database.

Local-first MCP proxy with BM25 tool discovery, quarantine security, Docker isolation, OAuth support, activity logging, and web UI. Routes multiple upstream MCP servers through a single endpoint.

Local ledger for development ports: leases a block of ports per project slot (one per working copy), renders env files, and resolves service names to URLs. No daemon, no listener.

MCP server for patent search and prior art discovery powered by Google Patents public dataset on BigQuery. Supports searching patents, fetching full patent details with CPC codes and citations, and retrieving legal claims text.

Figma MCP server with full read/write access via plugin bridge — no API token, no rate limits. 58 tools for design automation: styles, variables, components, prototypes, and content.

An MCP server that provides Claude Code with 99 methodology skills, seed patterns, decision logging, and memory tools to improve software development decisions. It acts as a cognitive scaffold layer, enabling better working methods rather than just additional data.

A Model Context Protocol server for Massdriver that enables AI assistants to manage infrastructure platform resources like projects, environments, deployments, policies, and more. It provides 106 tools and supports stdio or HTTP transports.

MCP server for Meshbrow that gives AI agents full browser automation capabilities with stealth anti-detection, enabling natural language control of browser sessions, data extraction, and multi-browser fleets.

The Terraform MCP Server is a Model Context Protocol (MCP) server that integrates seamlessly with Terraform Registry and HCP Terraform APIs, enabling advanced automation and interaction capabilities for Infrastructure as Code (IaC) development.

Connect your Umami Analytics to any MCP client to derive insights from natural language.

A command-line interface and MCP server for managing and monitoring multiple development services through a unified terminal UI. It enables users to interact with service logs, filter messages, and control development environments directly via Model Context Protocol integration.

An MCP (Model Context Protocol) server for managing Tailscale resources using the official Tailscale Go client library v2. This server provides complete coverage of the Tailscale API with enhanced, self-descriptive tools powered by OpenAPI documentation.

Enables AI assistants to inspect a Crossplane control plane read-only, discovering managed, composite and claim resources, tracing composition trees, and explaining failures with events and reasons. It also surfaces package health, composition definitions and validation, environment and runtime configs, and overall diagnostics across multiple clusters.

Production-ready MCP server designed to empower AI agents and LLMs to interact seamlessly with ClickHouse. It exposes your ClickHouse database as a set of standardized tools and resources that adhere to the MCP protocol, making it easy for agents built on OpenAI, Claude, or other platforms to query, explore, and analyse your data.

KSM MCP is a Model Context Protocol (MCP) server that acts as a secure intermediary between AI language models (like Claude) and Keeper Secrets Manager (KSM). It allows AI agents to manage your KSM secrets-such as listing, creating, retrieving, and deleting records and folders-while protecting your

Zero-dependency local proxy that wraps any MCP server to redact secrets, strip hidden-Unicode prompt injection, and block writes to protected paths like ~/.ssh and .env.

This project is intended as a both MCP server connecting to Kubernetes and a library to build more servers for any custom resources in Kubernetes.

An MCP server for TrueNAS SCALE that enables read-first management of storage, system, sharing, and virtualization resources with per-user API key authentication, and optional write operations.

Enables reading books from Project Gutenberg via MCP, with tools to search books, fetch metadata and full text, and retrieve passages by fixed-size keys.

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.