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Karthi Keyan
Karthi Keyan

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Why I Ditched ChatGPT and Cursor for OpenCode: A Smarter, Cheaper Way to Build AI Agents

#ai #opensource #cli #programming

As developers, we're always chasing efficiency—faster workflows, lower costs, and more control over our tools. For the longest time, I relied on proprietary AI chat platforms like ChatGPT, Cursor and Claude for quick prototyping, research, and even code generation. But let's be honest: they're convenient, but they're also inefficient and surprisingly expensive in the long run. If you're tired of opaque pricing, vendor lock-in, and limited customization, it's time to explore open-source alternatives like OpenCode. In this post, I'll share why I made the switch, how OpenCode saves you money with bring-your-own-keys (BYOK), and a simple hack to add web search functionality using Tavily's MCP integration. 🚀

This won't take more than 5 - 10 minutes, bookmark this blog & read this blog when you are free

The Hidden Costs of Proprietary AI Chats

Platforms like ChatGPT (from OpenAI) and Claude (from Anthropic) are fantastic for casual use. You log in, type a prompt, and get instant results. But dig deeper, and the inefficiencies pile up:

  • Overhead and Inefficiency: Every interaction routes through their servers, which means latency from network hops, rate limits during peak times, and no direct control over the underlying models. If you're building agents or automating tasks, you're constantly context-switching between the chat interface and your IDE—copy-pasting code, debugging in isolation, and losing productivity. 😩

  • Cost Creep: Subscriptions seem affordable at first (e.g., $20/month for ChatGPT Plus), but they scale poorly. Heavy users hit token limits quickly, leading to upgrades or per-API-call billing. Worse, you're paying for bundled features you might not need, like image generation or voice modes. In my experience, what starts as "just a quick query" balloons into hundreds of dollars annually—especially if you're experimenting with multiple models. 💸

  • Lack of Flexibility: You're locked into their ecosystem. Want to swap models mid-project? Tough luck without rewriting prompts. And forget about fine-tuning or integrating custom tools without jumping through hoops.

Enter OpenCode: an open-source AI code interpreter that flips the script by putting you in the driver's seat.

OpenCode: Bring Your Own Keys for Ultimate Control and Savings

OpenCode is a lightweight, local-first tool that turns your machine into a powerful AI agent hub. It's designed for developers who want to run AI models directly in their workflow—think VS Code or Cursor integration on steroids. Here's why it's a game-changer:

  • Bring Your Own Keys (BYOK): No more proprietary lock-in. OpenCode lets you plug in API keys from any provider, giving you access to a wide range of models without the middleman markup. 🔑

  • Cost-Effective with OpenRouter: One of my favorite integrations is OpenRouter, a model-agnostic API aggregator. You can purchase credits directly (starting as low as a few cents per million tokens) and route requests to the best/cheapest model for the job—be it Grok, GPT, Claude, or open-source options like Llama. For example:

    • Sign up at openrouter.ai.
    • Buy credits (e.g., $10 gets you millions of tokens depending on the model).
    • Add your OpenRouter API key to OpenCode's config.

This setup is way cheaper than flat subscriptions. I've cut my AI costs by 70% by optimizing model selection—using cheaper ones for simple tasks and premium for complex reasoning. 📉

  • Seamless Developer Workflow: OpenCode runs as an extension or standalone app, embedding AI right into your terminal or editor. It supports multi-model chaining, plan-mode execution, and even REPL-like interactions for iterative coding. No more tab-switching; everything happens in one place. 💻

But like any tool, it's not perfect. One key disadvantage? Out-of-the-box, OpenCode lacks built-in web search capabilities. Your agents can't fetch real-time data from the internet, which limits tasks like research or dynamic querying. Fortunately, this is easy to fix with MCP (Model Context Protocol) servers.

Adding Web Search to OpenCode with Tavily MCP

MCP is OpenCode's extensible protocol for integrating external tools, and Tavily (an AI-optimized search API) has an official MCP server that's dead simple to set up. This adds robust web search to your agents—think semantic queries, factual summaries, and citations—all without leaving your workflow. 🔍

Here's how to do it on Fedora Linux (tested on Fedora 42 as of November 2025):

  1. Get a Tavily API Key: Sign up at https://app.tavily.com/ and grab a free dev key (1,000 credits/month—enough for hundreds of searches). For example: tvly-dev-YourKeyHere.

  2. Configure Globally in OpenCode: OpenCode uses a global config file for MCP servers, located at ~/.config/opencode/opencode.jsonc (the .jsonc extension allows comments for clarity). If the file doesn't exist, create it:

mkdir -p ~/.config/opencode
touch ~/.config/opencode/opencode.jsonc
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Open the file in your editor (e.g., nano ~/.config/opencode/opencode.jsonc) and add this:

 {
     "$schema": "https://opencode.ai/config.json",
     "mcp": {
       "tavily": {
         "type": "remote",
         "url": "https://mcp.tavily.com/mcp/?tavilyApiKey=tvly-dev-YourKeyHere",  // Replace with your actual key
         "enabled": true
       }
     }
   }
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Save and restart OpenCode.

  1. Test It Out: In OpenCode, start a new session and prompt something like: "Search the web for the latest Fedora updates." Your agent will use Tavily's tavily_search tool to fetch real-time results with sources. Boom—web-enabled AI at no extra cost beyond Tavily's credits.

This setup transforms OpenCode from a solid code interpreter into a full-fledged research agent, all while keeping costs low and control high.

Wrapping Up: Make the Switch Today

If you're still grinding through Perplexity tabs or Gemini conversations, give OpenCode a shot. It's free, open-source, and empowers you to build cost-effective AI workflows with BYOK and OpenRouter integrations. Sure, adding features like search requires a quick config tweak—but that's the beauty of open tools: they're hackable.

I've been using this stack for months, and it's saved me time and money. Download OpenCode from https://opencode.ai/, grab those keys, and start experimenting. Questions? Drop a comment below—I'd love to hear your setups!

My blog is just a starting point, the possibilites are endless. What open-source AI tools are you using? Share in the comments! 🌟

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