{"slug": "i-built-an-llm-gateway-that-extends-claude-pro-max-users-with-azure-ai-foundry", "title": "I Built an LLM Gateway That Extends Claude Pro/Max Users with Azure AI Foundry, Amazon Bedrock, Local Models", "summary": "A developer built Lynkr, an open-source LLM gateway that extends Claude Pro/Max usage by routing different coding tasks to appropriate models across Azure AI Foundry, Amazon Bedrock, and local models. The gateway aims to solve inefficiencies in AI coding tools by separating premium reasoning tasks from cheap, frequent requests, enabling cost optimization and provider fallback.", "body_md": "AI coding tools have gotten very good.\n\nBut the infrastructure behind them is still weirdly inefficient.\n\nMost tools assume one provider, one lane, one billing path.\n\nThat means the same expensive model or subscription ends up handling everything:\n\nThat is the wrong abstraction.\n\nA coding workflow is not one type of problem. So it should not be forced through one type of model path.\n\nThat idea is what pushed me to build **Lynkr**.\n\n**Lynkr is an open-source LLM gateway for AI coding tools** that lets me combine:\n\nbehind one routing layer.\n\nIf you use a premium coding assistant every day, you have probably seen this already.\n\nA lot of the workload is not actually premium reasoning work.\n\nFor example:\n\nThese are useful requests, but they are not the same as:\n\nYet most tools send both classes of work through the same expensive path.\n\nThat creates three problems:\n\nIf a subscription-backed or premium model handles every tiny prompt, you burn good capacity on low-value tasks.\n\nEven if you already have access to Azure, AWS, or local models, your coding workflow is often tied to one vendor path.\n\nIf one provider is rate-limited, degraded, or just not the best fit for a task, you have no routing layer to adjust.\n\nLynkr sits between AI coding tools and model providers.\n\nIt works as an **LLM gateway**, which means the coding tool talks to Lynkr, and Lynkr decides what to do next.\n\nThat lets the gateway:\n\nThe part I am most excited about is hybrid routing across:\n\nThe simplest version looks like this:\n\nSo instead of replacing Claude, Azure, or Bedrock, the gateway combines them.\n\nThis is the key idea: **extend your Claude Pro/Max usage instead of burning it on everything**.\n\nImagine a coding session that looks like this:\n\n\"Read the auth middleware and summarize it.\"\n\nRoute to a cheap local model.\n\n\"Search all routes that call this helper.\"\n\nStill cheap/local.\n\n\"Refactor this auth flow to support tenant isolation.\"\n\nRoute to Claude Pro/Max.\n\n\"Generate an enterprise-safe variant for our internal stack.\"\n\nRoute to Azure AI Foundry.\n\n\"Azure is unavailable or rate-limited.\"\n\nFallback to Bedrock.\n\nThat is a much more natural way to run coding agents than pretending every prompt deserves the same model path.\n\nThis combination matters because each lane solves a different problem.\n\nGreat for high-quality coding and reasoning tasks where you already have subscription value.\n\nUseful when a team wants enterprise-hosted models, internal approvals, or Azure-aligned infrastructure.\n\nUseful for AWS-native orgs, alternate model access, or fallback when you want another enterprise provider path.\n\nUseful for cheap, frequent, low-stakes tasks that should not consume premium capacity at all.\n\nPutting these together in one gateway gives you a better operational model than any one of them alone.\n\nI think coding is one of the best use cases for an LLM gateway because coding workflows are:\n\nThat means a gateway can add value in several ways.\n\nNot every prompt deserves the same model.\n\nCheap requests stay cheap.\n\nPremium capacity gets reserved for tasks that actually need it.\n\nTeams can use Azure AI Foundry or Bedrock where policy or procurement matters.\n\nIf one provider path fails, the workflow can continue.\n\nAnother reason this matters is MCP and agentic tooling.\n\nAs coding tools become more agentic, they use more:\n\nThat creates a lot of overhead and a lot of repeated context.\n\nA gateway is the right place to optimize that.\n\nThat is also why I think the future is not just better models.\n\nIt is better **routing, caching, tool handling, and workload separation** around those models.\n\nI did not want just another OpenAI-compatible endpoint.\n\nI wanted a gateway that could actually help with real coding economics and workflow design.\n\nFor me, that means:\n\nI think this is especially useful for:\n\nI do not think the next big improvement in AI coding comes only from stronger base models.\n\nA lot of value will come from better infrastructure around them:\n\nThat is the direction I am building toward with **Lynkr**.\n\nGitHub: [https://github.com/Fast-Editor/Lynkr](https://github.com/Fast-Editor/Lynkr)\n\nPs:- This is fully following Anthropic TOS because lynkr wraps around your existing claude code", "url": "https://wpnews.pro/news/i-built-an-llm-gateway-that-extends-claude-pro-max-users-with-azure-ai-foundry", "canonical_source": "https://dev.to/lynkr/i-built-an-llm-gateway-that-extends-claude-promax-with-azure-ai-foundry-and-amazon-bedrock-1efb", "published_at": "2026-06-30 22:28:50+00:00", "updated_at": "2026-06-30 22:48:59.621998+00:00", "lang": "en", "topics": ["large-language-models", "developer-tools", "ai-infrastructure", "ai-agents", "generative-ai"], "entities": ["Lynkr", "Claude Pro", "Claude Max", "Azure AI Foundry", "Amazon Bedrock", "OpenAI"], "alternates": {"html": "https://wpnews.pro/news/i-built-an-llm-gateway-that-extends-claude-pro-max-users-with-azure-ai-foundry", "markdown": "https://wpnews.pro/news/i-built-an-llm-gateway-that-extends-claude-pro-max-users-with-azure-ai-foundry.md", "text": "https://wpnews.pro/news/i-built-an-llm-gateway-that-extends-claude-pro-max-users-with-azure-ai-foundry.txt", "jsonld": 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