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Bota provides a set of resources designed for AI-assisted development. Whether you’re using Claude, Cursor, GitHub Copilot, or any other AI coding assistant, these tools help the model understand the Bota API accurately.

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LLM Reference Docs

Two machine-readable files are available at well-known URLs, following the llmstxt.org standard:

llms.txt

Link index — one line per doc page. Use when you want an agent to discover and fetch individual pages.

llms-full.txt

Full reference — the entire API in one document, with canonical flows, gotchas, and code examples. Fetch once and the agent knows the full API.
How to use in Cursor or Claude Code: 
@https://docs.bota.dev/llms-full.txt

How do I set up streaming upload for a 4G device?

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Skills

Skills are self-contained integration guides — one per common task — with working code, step-by-step instructions, and a gotchas section. Drop one into your AI assistant’s context and it can implement the integration without hallucinating.

Device Registration

Register a device, bind to an end user, handle reassignment and lifecycle

Recording Upload

Create a recording, get a presigned URL, upload to S3, complete

Webhook Handling

Register an endpoint, verify HMAC-SHA256 signatures, handle retries

Auto-Processing

Enable zero-code transcription and summary pipeline

Streaming Upload

Upload audio chunks during recording for faster time-to-transcript
How to use: 
@https://raw.githubusercontent.com/bota-dev/bota-skills/main/recording-upload/skill.md

Implement recording upload in my Express backend
All skills are open source in github.com/bota-dev/bota-skills.

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MCP Server

The Bota MCP server connects your AI assistant directly to your Bota project — list devices, inspect recordings, trigger test webhooks, and more without leaving your IDE. You can also issue scoped tokens so end users can query their own recordings with an AI assistant.

MCP Server

Developer tier (full project access) and end user tier (scoped to their recordings)