Lightweight interface for SPARK-related analyses enabling AdaCore tooling with ongoing development and proof-of-concept features.

Read, search, and manipulate Git repositories with safe AI-driven workflows, emphasizing navigation, history insights, and auditable edits.

Vercel-based MCP server template with Redis-backed state and Fluid Compute for fast, configurable AI agents.

model context protocol mcp with next js

Demonstrates cross-source tool overrides through a compact tester that simulates conflicting tools from multiple providers.

Next.js 15 app with an integrated AI agent powered by CopilotKit and a context-aware backend client, featuring a responsive sidebar and Tailwind UI.

Zero-burden MCP server enabling CRUD on MySQL with read-only mode and optional query plan checks, DSN support, minimal runtime

Kotlin Multiplatform mobile client with pluggable providers for seamless AI tool integration on Android.

Real-time Airthings data insights via MCP with Claude Desktop integration.

Model Context Protocol (MCP) server for Avexa.ai, enabling real-time context orchestration between AI models and internal apis.

Cloud-agnostic analytics SDK for MCP servers enabling seamless event tracking and tool execution metrics.

Serverless context tooling on Vercel using Supabase with typed quote-editing tools, direct API fallbacks, and edge-friendly data handling.

Next.js-based MCP example using Vercel adapter with SSE transport, Redis backend, and Fluid Compute support.

Comprehensive, example-rich guide showing how AI models connect to data sources and tools via a standardized interface, with TypeScript/Python demos and real-world integrations.

Index is the single source of truth for Model Context Protocol (MCP) packages.

Educational web app demonstrating interactive tool usage and data access via an intuitive interface.

Discussions and README for MCP Registry (Model Context Protocol)

Semantic Kernel Model Context Protocol Client and Server Demo

Next.js-based MCP template featuring Redis-backed state, fluid compute support, and a ready-made client for quick testing on Vercel. It emphasizes type safety, modular prompts, and straightforward deployment, enabling rapid experimentation and scalable AI agent orchestration.

Redis-backed context engine on Vercel using Functions, enabling scalable tool orchestration with a TypeScript SDK.

Vercel-based template with Redis-backed state and Fluid Compute for fast, scalable context tooling deployment.

A Next.js-based example for Model Context Protocol featuring on- and off-chain Nad.fun tools, SSE streaming, and easy extensibility on Monad Testnet.

Bootstraps a new project with automated scaffolding, tool integration, and configurable templates.

Real-time neural signal processing integrated with standardized AI data exchange enables secure, composable brain-computer workflows.