Lynkr
Streamline your workflow with Lynkr, a CLI tool that acts as an HTTP proxy for efficient code interactions using Claude Code CLI.
What is Lynkr?
Lynkr is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to streamline your workflow with lynkr, a cli tool that acts as an http proxy for efficient code interactions using claude code cli.
Streamline your workflow with Lynkr, a CLI tool that acts as an HTTP proxy for efficient code interactions using Claude Code CLI.
This server falls under the Developer Tools category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- Streamline your workflow with Lynkr, a CLI tool that acts as
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx lynkrConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Lynkr
Lynkr is a token-compression HTTP proxy that sits between your AI coding tool and your LLM provider, delivering up to 87.6% fewer tokens on JSON tool results and 53% overall reduction on tool-heavy requests. It supports 13+ LLM providers including Ollama, OpenRouter, AWS Bedrock, and Databricks, and adds a semantic cache with 171ms average hit latency. Teams use it to dramatically cut inference costs for Claude Code, Cursor, and similar tools without changing a single line of application code.
Prerequisites
- Node.js 20 or later installed
- An LLM provider account (Ollama for local, or API key for OpenRouter/Bedrock/Databricks)
- An MCP-compatible client such as Claude Code CLI or Cursor
- npm available for global package installation
Install Lynkr globally
Install the lynkr package from npm so the CLI is available system-wide.
npm install -g lynkrCreate a .env configuration file
Run lynkr start once to generate the default .env template, then edit it to set your provider. For local testing with Ollama, set MODEL_PROVIDER=ollama. For production, set MODEL_PROVIDER=openrouter and add your OPENROUTER_API_KEY.
# Ollama (local/free)
MODEL_PROVIDER=ollama
OLLAMA_ENDPOINT=http://localhost:11434
OLLAMA_MODEL=qwen2.5-coder:latest
PORT=8081
FALLBACK_ENABLED=false
POLICY_SAFE_COMMANDS_ENABLED=false
# OR OpenRouter (cloud)
# MODEL_PROVIDER=openrouter
# OPENROUTER_API_KEY=sk-or-v1-your-key-here
# PORT=8081Start the Lynkr proxy server
Launch the Lynkr proxy. It listens on the port you set (default 8081) and compresses all tool call traffic passing through it.
lynkr startPoint Claude Code at Lynkr
Set the ANTHROPIC_BASE_URL environment variable to the Lynkr proxy address. Set ANTHROPIC_API_KEY to any dummy value because Lynkr handles auth with the downstream provider.
export ANTHROPIC_BASE_URL=http://localhost:8081
export ANTHROPIC_API_KEY=dummy
claude "write a hello world in python"Enable semantic caching (optional)
Add caching variables to your .env to activate the 171ms semantic cache and prompt cache for repeat queries.
PROMPT_CACHE_ENABLED=true
SEMANTIC_CACHE_ENABLED=trueLynkr Examples
Client configuration
Claude Desktop config to route all requests through Lynkr running locally on port 8081.
{
"mcpServers": {},
"env": {
"ANTHROPIC_BASE_URL": "http://localhost:8081",
"ANTHROPIC_API_KEY": "dummy"
}
}Prompts to try
Typical Claude Code tasks that benefit from Lynkr's token compression on JSON tool results.
- "Refactor this module to use async/await throughout"
- "Run the test suite and summarize any failures"
- "List all TODO comments in the codebase and create issues for each"
- "Explain the architecture of this repository"Troubleshooting Lynkr
lynkr: command not found after npm install -g
Check that your npm global bin directory is on your PATH. Run `npm bin -g` to find it and add it to your shell profile (e.g., export PATH="$(npm bin -g):$PATH").
API calls fail with authentication errors
Ensure ANTHROPIC_API_KEY is set to any non-empty string (e.g., 'dummy') in your shell, and that ANTHROPIC_BASE_URL points exactly to http://localhost:8081 (no trailing slash). Also verify lynkr start is running and your .env provider credentials are correct.
Ollama model not found or connection refused
Make sure Ollama is running (`ollama serve`) and the model is pulled before starting Lynkr: `ollama pull qwen2.5-coder:latest`. Confirm OLLAMA_ENDPOINT matches the address Ollama actually listens on.
Frequently Asked Questions about Lynkr
What is Lynkr?
Lynkr is a Model Context Protocol (MCP) server that streamline your workflow with lynkr, a cli tool that acts as an http proxy for efficient code interactions using claude code cli. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Lynkr?
Follow the installation instructions on the Lynkr GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Lynkr?
Lynkr works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Lynkr free to use?
Yes, Lynkr is open source and available under the Apache-2.0 license. You can use it freely in both personal and commercial projects.
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Quick Config Preview
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