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‎README.md‎

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> **Production-ready Claude Code proxy server supporting Databricks, OpenRouter, Ollama & Azure. Features MCP integration, prompt caching & 60-80% token optimization savings.**
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## 🔖 Keywords
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`claude-code` `claude-proxy` `anthropic-api` `databricks-llm` `openrouter-integration` `ollama-local` `llama-cpp` `azure-openai` `azure-anthropic` `mcp-server` `prompt-caching` `token-optimization` `ai-coding-assistant` `llm-proxy` `self-hosted-ai` `git-automation` `code-generation` `developer-tools` `ci-cd-automation` `llm-gateway` `cost-reduction` `multi-provider-llm`
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---
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## Table of Contents
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1. [Why Lynkr?](#why-lynkr)
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2. [Quick Start (3 minutes)](#quick-start-3-minutes)
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3. [Overview](#overview)
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4. [Supported Models & Providers](#supported-models--providers)
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4. [Supported AI Model Providers](#supported-ai-model-providers-databricks-openrouter-ollama-azure-llamacpp)
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5. [Lynkr vs Native Claude Code](#lynkr-vs-native-claude-code)
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6. [Core Capabilities](#core-capabilities)
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- [Repo Intelligence & Navigation](#repo-intelligence--navigation)
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- [Execution & Tooling](#execution--tooling)
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- [Workflow & Collaboration](#workflow--collaboration)
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- [UX, Monitoring, and Logs](#ux-monitoring-and-logs)
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7. [Production Hardening Features](#production-hardening-features)
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7. [Production-Ready Features for Enterprise Deployment](#production-ready-features-for-enterprise-deployment)
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- [Reliability & Resilience](#reliability--resilience)
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- [Observability & Monitoring](#observability--monitoring)
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- [Security & Governance](#security--governance)
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8. [Architecture](#architecture)
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9. [Getting Started](#getting-started)
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9. [Getting Started: Installation & Setup Guide](#getting-started-installation--setup-guide)
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10. [Configuration Reference](#configuration-reference)
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11. [Runtime Operations](#runtime-operations)
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- [Launching the Proxy](#launching-the-proxy)
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12. [Manual Test Matrix](#manual-test-matrix)
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13. [Troubleshooting](#troubleshooting)
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14. [Roadmap & Known Gaps](#roadmap--known-gaps)
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15. [FAQ](#faq)
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16. [References](#references)
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17. [License](#license)
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15. [Frequently Asked Questions (FAQ)](#frequently-asked-questions-faq)
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16. [References & Further Reading](#references--further-reading)
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17. [Community & Adoption](#community--adoption)
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18. [License](#license)
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### The Solution
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Lynkr is a **production-ready proxy server** that unlocks Claude Code CLI's full potential:
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- ✅ **Any LLM Provider** - Databricks, OpenRouter (100+ models), Ollama (local), Azure, OpenAI, llama.cpp
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- ✅ **60-80% Cost Reduction** - Built-in token optimization (5 optimization phases implemented)
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- ✅ **Zero Code Changes** - Drop-in replacement for Anthropic backend
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- ✅ **Local & Offline** - Run Claude Code with Ollama or llama.cpp (no internet required)
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- ✅ **Enterprise Features** - Circuit breakers, load balancing, metrics, K8s-ready health checks
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- ✅ **MCP Integration** - Automatically discover and orchestrate Model Context Protocol servers
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- ✅ **Privacy & Control** - Self-hosted, open-source (Apache 2.0), no vendor lock-in
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- ✅ **Any LLM Provider** - [Databricks, OpenRouter (100+ models), Ollama (local), Azure, OpenAI, llama.cpp](#supported-ai-model-providers-databricks-openrouter-ollama-azure-llamacpp)
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- ✅ **60-80% Cost Reduction** - Built-in [token optimization](#token-optimization-implementation) (5 optimization phases implemented)
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- ✅ **Zero Code Changes** - [Drop-in replacement](#connecting-claude-code-cli) for Anthropic backend
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- ✅ **Local & Offline** - Run Claude Code with [Ollama](#using-ollama-models) or [llama.cpp](#using-llamacpp-with-lynkr) (no internet required)
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- ✅ **Enterprise Features** - [Circuit breakers, load balancing, metrics, K8s-ready health checks](#production-ready-features-for-enterprise-deployment)
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- ✅ **MCP Integration** - Automatically discover and orchestrate [Model Context Protocol servers](#integrating-mcp-servers)
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- ✅ **Privacy & Control** - Self-hosted, open-source ([Apache 2.0](#license)), no vendor lock-in
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### Perfect For
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- 🔧 **Developers** who want flexibility and cost control
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## Supported Models & Providers
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## Supported AI Model Providers (Databricks, OpenRouter, Ollama, Azure, llama.cpp)
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Lynkr supports multiple AI model providers, giving you flexibility in choosing the right model for your needs:
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|----------|--------------|------------------|----------|
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| **Databricks** (Default) | `MODEL_PROVIDER=databricks` | Claude Sonnet 4.5, Claude Opus 4.5 | Production use, enterprise deployment |
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| **OpenAI** | `MODEL_PROVIDER=openai` | GPT-5, GPT-5.2, GPT-4o, GPT-4o-mini, GPT-4-turbo, o1, o1-mini | Direct OpenAI API access |
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| **Azure OpenAI** | `MODEL_PROVIDER=azure-openai` | GPT-5, GPT-5.2,GPT-4o, GPT-4o-mini, GPT-5, o1, o3 | Azure integration, Microsoft ecosystem |
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| **Azure OpenAI** | `MODEL_PROVIDER=azure-openai` | GPT-5, GPT-5.2,GPT-4o, GPT-4o-mini, GPT-5, o1, o3, Kimi-K2 | Azure integration, Microsoft ecosystem |
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| **Azure Anthropic** | `MODEL_PROVIDER=azure-anthropic` | Claude Sonnet 4.5, Claude Opus 4.5 | Azure-hosted Claude models |
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| **OpenRouter** | `MODEL_PROVIDER=openrouter` | 100+ models (GPT-4o, Claude, Gemini, Llama, etc.) | Model flexibility, cost optimization |
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| **Ollama** (Local) | `MODEL_PROVIDER=ollama` | Llama 3.1, Qwen2.5, Mistral, CodeLlama | Local/offline use, privacy, no API costs |
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### **Azure OpenAI Specific Models**
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When using `MODEL_PROVIDER=azure-openai`, you can deploy any of these models:
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When using `MODEL_PROVIDER=azure-openai`, you can deploy any of the models in azure ai foundry:
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| Model | Deployment Name | Capabilities | Best For |
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|-------|----------------|--------------|----------|
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| **GPT-4o** | `gpt-4o` | Text, vision, function calling | General-purpose, multimodal tasks |
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| **GPT-4o-mini** | `gpt-4o-mini` | Text, function calling | Fast responses, cost-effective |
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| **GPT-5** | `gpt-5-chat` or custom | Advanced reasoning, longer context | Complex problem-solving |
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| **o1-preview** | `o1-preview` | Deep reasoning, chain of thought | Mathematical, logic problems |
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| **o3-mini** | `o3-mini` | Efficient reasoning | Fast reasoning tasks |
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**Note**: Azure OpenAI deployment names are configurable via `AZURE_OPENAI_DEPLOYMENT` environment variable.
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## 🚀 Ready to Get Started?
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**Reduce your Claude Code costs by 60-80% in under 3 minutes:**
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1. ⭐ **[Star this repo](https://github.com/vishalveerareddy123/Lynkr)** to show support and stay updated
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2. 📖 **[Follow the Quick Start Guide](#quick-start-3-minutes)** to install and configure Lynkr
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3. 💬 **[Join the Discussion](https://github.com/vishalveerareddy123/Lynkr/discussions)** for community support
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4. 🐛 **[Report Issues](https://github.com/vishalveerareddy123/Lynkr/issues)** to help improve Lynkr
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---
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## Core Capabilities
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### Long-Term Memory System (Titans-Inspired)
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## Production Hardening Features
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## Production-Ready Features for Enterprise Deployment
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Lynkr includes comprehensive production-ready features designed for reliability, observability, and security in enterprise environments. These features add minimal performance overhead while providing robust operational capabilities.
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Lynkr includes comprehensive production-hardened features designed for reliability, observability, and security in enterprise environments. These features add minimal performance overhead while providing robust operational capabilities for mission-critical AI deployments.
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### Reliability & Resilience
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└───────────────────┘
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```
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### Request Flow Diagram
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```mermaid
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graph TB
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A[Claude Code CLI] -->|HTTP POST /v1/messages| B[Lynkr Proxy Server]
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B --> C{Middleware Stack}
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C -->|Load Shedding| D{Load OK?}
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D -->|Yes| E[Request Logging]
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D -->|No| Z1[503 Service Unavailable]
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E --> F[Metrics Collection]
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F --> G[Input Validation]
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G --> H[Orchestrator]
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H --> I{Check Prompt Cache}
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I -->|Cache Hit| J[Return Cached Response]
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I -->|Cache Miss| K{Determine Provider}
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K -->|Simple 0-2 tools| L[Ollama Local]
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K -->|Moderate 3-14 tools| M[OpenRouter / Azure]
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K -->|Complex 15+ tools| N[Databricks]
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L --> O[Circuit Breaker Check]
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M --> O
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N --> O
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O -->|Closed| P{Provider API}
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O -->|Open| Z2[Fallback Provider]
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P -->|Databricks| Q1[Databricks API]
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P -->|OpenRouter| Q2[OpenRouter API]
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P -->|Ollama| Q3[Ollama Local]
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P -->|Azure| Q4[Azure Anthropic API]
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Q1 --> R[Response Processing]
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Q2 --> R
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Q3 --> R
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Q4 --> R
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Z2 --> R
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R --> S[Format Conversion]
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S --> T[Cache Response]
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T --> U[Update Metrics]
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U --> V[Return to Client]
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J --> V
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style B fill:#4a90e2,stroke:#333,stroke-width:2px,color:#fff
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style H fill:#7b68ee,stroke:#333,stroke-width:2px,color:#fff
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style K fill:#f39c12,stroke:#333,stroke-width:2px
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style P fill:#2ecc71,stroke:#333,stroke-width:2px,color:#fff
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```
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**Key Components:**
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- **`src/api/router.js`** – Express routes that accept Claude-compatible `/v1/messages` requests.
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- **`src/api/middleware/*`** – Production middleware stack:
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- `load-shedding.js` – Proactive overload protection with resource monitoring
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## Getting Started
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## Getting Started: Installation & Setup Guide
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### Prerequisites
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## References
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## References & Further Reading
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Lynkr's design also includes ACE Framework informed by research in agentic AI systems and context engineering:
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### Academic & Technical Resources
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**Agentic AI Systems:**
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- **Zhang et al. (2024)**. *Agentic Context Engineering*. arXiv:2510.04618. [arXiv](https://arxiv.org/abs/2510.04618)
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**Long-Term Memory & RAG:**
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- **Mohtashami & Jaggi (2023)**. *Landmark Attention: Random-Access Infinite Context Length for Transformers*. [arXiv](https://arxiv.org/abs/2305.16300)
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- **Google DeepMind (2024)**. *Titans: Learning to Memorize at Test Time*. [arXiv](https://arxiv.org/abs/2411.07043)
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For BibTeX citations, see [CITATIONS.bib](CITATIONS.bib).
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### Official Documentation
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- [Claude Code CLI Documentation](https://docs.anthropic.com/en/docs/build-with-claude/claude-for-sheets) - Official Claude Code reference
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- [Model Context Protocol (MCP) Specification](https://spec.modelcontextprotocol.io/) - MCP protocol documentation
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- [Databricks Foundation Models](https://docs.databricks.com/en/machine-learning/foundation-models/index.html) - Databricks LLM documentation
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- [Anthropic API Documentation](https://docs.anthropic.com/en/api/getting-started) - Claude API reference
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### Related Projects & Tools
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- [Ollama](https://ollama.ai/) - Local LLM runtime for running open-source models
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- [OpenRouter](https://openrouter.ai/) - Multi-provider LLM API gateway (100+ models)
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- [llama.cpp](https://github.com/ggerganov/llama.cpp) - High-performance C++ LLM inference engine
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- [LiteLLM](https://github.com/BerriAI/litellm) - Multi-provider LLM proxy (alternative approach)
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- [Awesome MCP Servers](https://github.com/punkpeye/awesome-mcp-servers) - Curated list of MCP server implementations
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---
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## Community & Adoption
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### Get Involved
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**⭐ Star this repository** to show your support and help others discover Lynkr!
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[![GitHub stars](https://img.shields.io/github/stars/vishalveerareddy123/Lynkr?style=social)](https://github.com/vishalveerareddy123/Lynkr)
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### Support & Resources
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- 🐛 **Report Issues:** [GitHub Issues](https://github.com/vishalveerareddy123/Lynkr/issues) - Bug reports and feature requests
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- 💬 **Discussions:** [GitHub Discussions](https://github.com/vishalveerareddy123/Lynkr/discussions) - Questions, ideas, and community help
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- 📚 **Documentation:** [DeepWiki](https://deepwiki.com/vishalveerareddy123/Lynkr) - Comprehensive guides and examples
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- 🔧 **Contributing:** [CONTRIBUTING.md](CONTRIBUTING.md) - How to contribute to Lynkr
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### Share Lynkr
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Help spread the word about Lynkr:
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- 🐦 [Share on Twitter](https://twitter.com/intent/tweet?text=Check%20out%20Lynkr%20-%20a%20production-ready%20Claude%20Code%20proxy%20with%20multi-provider%20support%20and%2060-80%25%20token%20savings!&url=https://github.com/vishalveerareddy123/Lynkr&hashtags=AI,ClaudeCode,LLM,OpenSource)
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- 💼 [Share on LinkedIn](https://www.linkedin.com/sharing/share-offsite/?url=https://github.com/vishalveerareddy123/Lynkr)
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- 📰 [Share on Hacker News](https://news.ycombinator.com/submitlink?u=https://github.com/vishalveerareddy123/Lynkr&t=Lynkr%20-%20Production-Ready%20Claude%20Code%20Proxy)
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- 📱 [Share on Reddit](https://www.reddit.com/submit?url=https://github.com/vishalveerareddy123/Lynkr&title=Lynkr%20-%20Production-Ready%20Claude%20Code%20Proxy%20with%20Multi-Provider%20Support)
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### Why Developers Choose Lynkr
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- 💰 **Massive cost savings** - Save 60-80% on token costs with built-in optimization
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- 🔓 **Provider freedom** - Choose from 7+ LLM providers (Databricks, OpenRouter, Ollama, Azure, llama.cpp)
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- 🏠 **Privacy & control** - Self-hosted, open-source, no vendor lock-in
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- 🚀 **Production-ready** - Enterprise features: circuit breakers, metrics, health checks
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- 🛠️ **Active development** - Regular updates, responsive maintainers, growing community
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## License

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