Otari Gateway Tames OpenCode Costs

Otari Gateway integrates with OpenCode to provide real-time cost tracking and budget controls for AI coding sessions, requiring no code changes.

Daniel Singer

Editor, StartupHub.ai

Jun 8 at 2:02 PMUpdated Aug 22, 20262 min read

Diagram showing Otari Gateway connecting OpenCode to AI model providers — The Otari Gateway facilitates cost and usage tracking for OpenCode AI sessions.· Mozilla Blog

Visual TL;DR

AI Coding Cost Black BoxDriver

From the articleAI coding can feel like a black box, leaving developers in the dark about session costs and resource consumption.

Otari GatewayCore

middleware between OpenCode and AI model providers

From the article 9+ mentionsThe new Otari Gateway OpenCode integration aims to change that by providing granular visibility and control over AI development workflows.

Integrates with OpenCodeContext

no code changes required for AI development workflows

From the article 5 mentionsOtari acts as a middleware, sitting between OpenCode and the underlying AI model provider.

Tames OpenCode CostsOutcome

streamlines AI development and controls expenses

Real-time Cost TrackingEffect

granular visibility into per-session cost tracking

From the articleThis allows for per-session cost tracking, budget enforcement, and detailed usage breakdowns without any application code modifications.

Budget ControlsEffect

enforces budgets for AI coding sessions

From the article 3 mentionsIt's part of a broader trend towards developers wanting more ownership and control over their AI stacks, as highlighted in pieces like Otari: Own Your AI Stack.

Detailed Usage BreakdownsEffect

logs token counts, model names, and timestamps

From the articleThis allows for per-session cost tracking, budget enforcement, and detailed usage breakdowns without any application code modifications.

AI coding can feel like a black box, leaving developers in the dark about session costs and resource consumption. The new Otari Gateway OpenCode integration aims to change that by providing granular visibility and control over AI development workflows.

Running models like Kimi K2.6, even with its substantial 256K context window, can quickly become an expensive affair. Otari acts as a middleware, sitting between OpenCode and the underlying AI model provider. This allows for per-session cost tracking, budget enforcement, and detailed usage breakdowns without any application code modifications.

The setup involves routing OpenCode requests through the Otari API endpoint. Otari resolves credentials server-side and logs essential metadata such as token counts, model names, and timestamps, ensuring user prompts and completions remain private.

Streamlining AI Development

Integrating Otari is a three-step process. First, users create an account and generate an API token on otari.ai. Optionally, provider API keys (for OpenAI, Anthropic, etc.) can be added to Otari's settings, allowing the gateway to make calls on the user's behalf.

The second step involves configuring OpenCode's `opencode.jsonc` file to point to the Otari gateway. This includes setting the `baseURL` to Otari's API endpoint and providing the generated API key. Environment variables are recommended for securely managing API keys.

Finally, users select the Otari-configured model within OpenCode to initiate coding sessions. Every interaction then flows through the Otari Gateway, providing immediate insights into usage and costs directly on the Otari dashboard.

This solution offers a crucial layer of financial and operational transparency for AI development, making it easier to manage expensive inference costs. It's part of a broader trend towards developers wanting more ownership and control over their AI stacks, as highlighted in pieces like Otari: Own Your AI Stack.

© 2026 StartupHub.ai. All rights reserved. You may not republish this article in full without a license. Search engines and AI research tools may crawl and summarize for reference. Bulk reproduction or model training requires a license. See our terms.

#Otari #OpenCode #AI Development #LLM Gateway #Cost Management

Written by

Daniel Singer

Editor, StartupHub.ai

Daniel Singer is the editor of StartupHub.ai, a technology expert and thought leader on AI and its applications across sectors, from fintech and healthcare to developer tooling and consumer software. He writes and tests the tools covered here thoroughly and regularly, and built StartupHub.ai to give founders, operators and buyers a clearer read on what they are actually being sold.