model context protocol mcp with vercel functions

Next.js MCP server sample using Vercel adapter with Redis SSE and Fluid Compute for scalable, serverless workflows.

Next.js example demonstrating prompt-and-tools routing via a Vercel adapter with Redis-backed SSE and Fluid Compute.

Redis-backed, Vercel-powered deployment template using Fluid Compute and TypeScript SDK for rapid prototyping.

Vercel-based MCP server template with Redis backing and Fluid Compute for scalable, serverless prompts.

Model Context Protocol

Model Context Protocol

Modular, multi-language AI framework enabling dynamic tool discovery and context-sharing across Java Spring Boot and Python services.

Django-based model context integration enabling seamless context propagation, dynamic adapters, and cross-service data sharing.

Python-based client-server suite enabling Claude-backed tool selection, arXiv and web search, plus iris prediction via a trained model.

Telegram-driven search assistant unifies YouTube and Google queries with fast async operations and secure API key management.

Asynchronous MCP server delivering US weather data via NWS API with FastMCP tool definitions for easy integration into chat agents and automation pipelines.

Python-based demonstration showcasing interactive tool endpoints, local LlamaIndex/Ollama integration, and a client-agent workflow for context-driven querying.

Streamlit-based learning path generator powered by MCP with YouTube, Drive, and Notion integrations for personalized study plans.

Extensible framework enabling LLMs to discover, connect, and orchestrate inbuilt and external tools.

model-context-protocol-info

Extensible MCP server enabling context-aware orchestration with pluggable backends and streamlined integration.

model context protocol_activity

Modular, secure, pluggable context management server for AI workflows with efficient serialization and isolation.

Modular MCP server with pluggable adapters, versioned contexts, and secure data exchange for reliable, extensible AI context management.

Offline-first, MCP-driven orchestration for specialized agents with a local LLM stack and elegant UI.

Comprehensive Python collection with modular tooling, resumable messaging, cancellation, and real-time updates for robust integrations.

A TypeScript-based server delivering dynamic model context with secure, scalable context management.

Dynamic model-context orchestration with secure isolation, pluggable adapters, and context-aware routing for advanced AI workflows.