"Developer tools for a NextJS and FastAPI tech stack with Firebase and Vercel" matching MCP servers:

Enables interaction with Firebase projects and services, including deployment, database management, authentication, and local emulation, through natural language.

Detects the technology stack behind any website, including frameworks, CMS, analytics, and more, via a single POST request.

Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.

A template for deploying an MCP server on Vercel, with example tools like roll_dice and get_weather.

Enables AI agents to search, filter, and monitor curated AI model API free credits and low-cost token promotions through eight tools, four resources, and three prompts — including finding deals expiring soon, checking eligibility and blocked conditions, and producing daily briefs.

Provides Clockchain's verified-time primitives, notarization, smart-contract scheduling, audit trails, and agent identity verification to any MCP client.

A local MCP server that integrates FastMCP with OpenAI to enable natural language queries for current weather, forecasts, and currency conversion using ExchangeRate-API and Open-Meteo.

Enables querying real-time adoption metrics, trends, and comparisons for popular AI coding tools like OpenAI SDK, Anthropic SDK, Cursor, GitHub Copilot, and LangChain through natural language.

Enables comprehensive Google Meet and Calendar management through Google Calendar API v3 and Google Meet API v2, supporting calendar event creation with Meet links, space management, transcription, recording, attendance tracking, and meeting moderation controls.

A TypeScript-based MCP server for handling a simple notes system with NextJS that supports creating and summarizing text notes using MCP concepts.

A zero-configuration tool that automatically converts FastAPI endpoints into Model Context Protocol (MCP) tools, enabling AI systems to interact with your API through natural language.

Enables serving REST APIs and MCP AI tools simultaneously from a single server, including converting existing FastAPI applications into MCP tools and defining endpoints that work as both REST routes and agent-callable tools.

A multi-tool AI assistant system that uses Model Context Protocol to connect language models with various tools, including math calculations and weather information.

A bridge that enables Large Language Models to read from and write to Firebase Firestore collections through Model Context Protocol (MCP) tools.

A read-only MongoDB MCP server designed for serverless deployment on Vercel, providing secure, limited access to MongoDB databases for AI assistants.

Run free live audience Q&A and polls from your agent: start an AskOne room, add and launch a poll, approve or hide questions and mark them answered, close the room, then read the questions as a FAQ draft and get the results. Free AI moderation. Uses an organization API token from askone.org

Enables AI coding assistants to inspect FastAPI applications, routers, and Pydantic models, including generating TypeScript interfaces and Zod schemas and discovering backend routes without hallucination.

Enables control and management of a self-hosted media stack (Radarr, Sonarr, Prowlarr, SABnzbd, qBittorrent) through natural language via MCP.

An MCP server providing 82 tools for persistent memory, governance, and consciousness continuity for AI instances. Enables local-first, runtime-reflexive operation with cross-device access and recursive self-awareness.

Enables LLM clients such as Cursor and Claude to discover and use generated REST services through MCP tools for create, update, and delete actions and MCP resources for list and get-by-id context. Services generated in one command are exposed simultaneously as REST endpoints and MCP tools and resources.

Enables AI assistants to interact with generated REST APIs by discovering and using CRUD tools and read-only data resources.

Enables AI assistants to discover and invoke CRUD tools and read-only resources over the Model Context Protocol for generated API services.

Exposes FastAPI routes as MCP tools with auto-discovery, Pydantic schema extraction, and built-in observability.

Enables managing Vercel projects, deployments, build logs, domains, and environment variables through natural language in Microsoft Copilot Studio, using streamable HTTP with API key authentication.

Enables AI assistants to interact directly with generated REST APIs by exposing CRUD operations as MCP tools and read-only data as resources.

Exposes generated CRUD services to LLM clients over the Model Context Protocol, providing tools for create, update, and delete actions plus read-only resources for listing and fetching records by id. It lets assistants like Claude, ChatGPT, and Cursor discover and manipulate the same data served by the project's REST endpoints without any extra glue code.

Exposes every generated CRUD service to LLM clients such as Claude, ChatGPT, or Cursor through discoverable MCP tools for create, update, and list actions plus read-only resources, so models can query and manipulate data without raw HTTP calls. It runs alongside the same codebase's REST endpoints, letting clients and AI share one data layer.

Enables LLMs to discover and invoke generated CRUD operations as MCP tools and read data through MCP resources, alongside standard REST endpoints, using one codebase.

Enables LLMs to discover and invoke generated CRUD tools and resources, allowing AI assistants to interact with the same data exposed by the REST API. Supports MCP clients such as Cursor and Claude over HTTP.

Enables LLMs to discover and invoke generated API actions as MCP tools and read context through MCP resources for list and get-by-id operations. It provides HTTP-based MCP access for clients such as Cursor and Claude without extra glue code.