"Latest Next.js Documentation" matching MCP servers:

A sample MCP server implementation for Next.js projects that uses the Vercel MCP Adapter to handle protocol requests across different transport methods.

A template MCP server built with Next.js using the Vercel MCP Adapter. Provides a framework for deploying MCP servers with custom tools, prompts, and resources on Vercel with SSE transport support.

Self-hostable MCP server for portable AI agent playbooks: manage skills, MCP configurations, personas, instructions, memory, and canvas documents. The public Next.js source implements Streamable HTTP MCP at /api/mcp/manage; users can run it with the repository's Dockerfile and their own database configuration.

Lets parallel DSH agent sessions on the same machine discover what each other is doing — which workspace, which tool is running, the latest human request and reply — so they can spot overlapping file edits and git races, and leave notes for one another on a shared append-only board.

Provides AI assistants with real-time access to the AGNO framework documentation by enabling them to browse, search, and fetch documentation pages. This server allows users to query information about AGNO's Agents, Teams, and Workflows directly through MCP-compatible clients.

MCP server for interacting with fal.ai models and services. Uses the latest streaming MCP support.

Recommends APIs to AI agents based on agent-readiness and use-case keyword overlap, returning structured endpoints and documentation to ground integration code.

A sample implementation of a Model Context Protocol server using Next.js and the Vercel MCP Adapter, allowing developers to create AI assistants with custom tools and resources.

Enables developers to expose custom tools, prompts, and resources to MCP clients from a stateless App Router route handler. Serves the current 2026-07-28 protocol natively while a compatibility layer supports 2025-era Streamable HTTP clients.

Enables universal access to MCP tools and capabilities from external clients, client-side, and server-side within a Next.js application.

Enables Claude Code to send prompts to signed-in ChatGPT and Gemini browser tabs and retrieve streamed replies as MCP tools without API keys. It also supports listing tabs, reading the latest response, scraping conversations, and checking connection health.

An MCP server built into a Next.js app that serves prompts via the Model Context Protocol, supporting local and cloud LLM providers.

Provides a trust layer for agent-to-agent commerce and delegated agent authority, allowing MCP-capable agents to install and fetch the latest Internet Court skill dynamically.

A sample implementation of Model Context Protocol server using Next.js and the Vercel MCP Adapter, allowing developers to create custom AI agent backends with tools, prompts, and resources.

CodeMesh enables AI agents to orchestrate any MCP server by writing TypeScript code, with self-improving capabilities through auto-augmentation of tool documentation.

Public MCP front door for Spala agent discovery, providing onboarding, documentation search, and template/addon listings for planning backend workflows.

A Node.js MCP server that loads plugins, registers tools via the MCP SDK, and exposes functionality over stdio with built-in persistence and a Next.js web UI. It provides a management stack for MCP tools with plugin lifecycle management and security controls.

Generates production-ready, white-labeled web architectures (Next.js + Supabase or static) from vertical packs and blueprints. Enables AI agents to scaffold inventory sites, SaaS platforms, and custom verticals, including Supabase provisioning, edge functions, and deployment.

A self-hostable, open-source, semantically-searchable Agent Skills registry delivered over MCP, with a three-tier progressive disclosure architecture.

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.