dot2api: Open-Source Proxy Wrapping OpenAI Always-On Agent Dots into Standard API Endpoints
An architectural overview of dot2api, an open-source proxy wrapping OpenAI's GPT-6 Astra-powered always-on agent Dots into OpenAI and Claude-compatible API endp
Open-source developer @Pluvio9yte has released 'dot2api', a developer proxy that transforms OpenAI's always-on agent 'Dots' into standard, programmatic API endpoints. By intercepting triggers through Model Context Protocol (MCP) connectors, the tool wraps the standalone agent into standard OpenAI and Anthropic Claude-compatible interfaces, enabling seamless integration into external automated pipelines.
Introduced at DevDay 2026, Dots is OpenAI's autonomous always-on agent powered by the flagship GPT-6 Astra model. Operating in a cloud-hosted sandbox equipped with browsing and execution environments, Dots is designed to persist tasks 24/7 without directly consuming standard ChatGPT conversational quotas. However, because OpenAI provides no standalone public REST API endpoint for Dots, developers were previously confined to interacting with the agent through proprietary chat interfaces.
Architectural Context: OpenAI Dots and the Lack of Independent APIs
OpenAI engineered Dots as a persistent assistant that moves beyond turn-based chat sessions, continuing background tasks even after a user closes their desktop or browser window.
- GPT-6 Astra Foundation: Driven by OpenAI's next-generation reasoning model, GPT-6 Astra, Dots operates inside an isolated cloud sandbox with integrated web search and tool execution capabilities.
- Quota Separation Model: General conversational interactions with Dots do not deduct from regular ChatGPT tier quotas. Only when Dots coordinates external Codex coding jobs or enterprise Work workflows are those respective product allotments consumed.
- Absence of Direct API Interfaces: Despite its autonomous execution capabilities, OpenAI did not roll out dedicated REST API endpoints for Dots on its developer platform, creating an integration barrier for developers building external automation stacks like n8n or autonomous agent relays.
MCP Connector Bridging and Standard API Wrapping in dot2api
The dot2api proxy circumvents this interface barrier by tapping into the Model Context Protocol (MCP) connectors and plugin channels that Dots uses to interact with external tools.
While Dots does not expose incoming REST endpoints directly, it listens for external wake-up events and execution triggers dispatched across registered MCP connectors. dot2api acts as an intermediary bridge, structuring these communication pathways into familiar API specifications.
- Dual Standard Protocol Compatibility: The proxy exposes endpoints compatible with standard OpenAI and Anthropic Claude API specifications.
- Bidirectional Event Translation: When an external application dispatches a standard payload, the proxy formats the request into an MCP task payload, passes it to Dots, awaits processing, and serializes the agent's output back into standardized JSON responses.
- Zero Additional Inference Overhead: Because the relay service handles routing, state tracking, and payload formatting without executing standalone foundation models locally, it introduces no additional inference costs.
Practical Integration Scenarios for Automation Pipelines
By establishing a standard REST interface over Dots, dot2api allows developers to connect the agent into existing software workflows that natively support HTTP-based LLMs.
- n8n and Low-Code Workflow Automation: Developers can configure standard OpenAI HTTP nodes in n8n with dot2api credentials, delegating recurring data aggregation, market tracking, or document summarization directly to Dots.
- Scheduled Cron Batch Jobs: Scripts running automated health checks, web scraping, or daily reporting routines can invoke Dots programmatically on fixed schedules.
- Messaging Bot Integration: The proxy allows developers to bridge conversational agents into custom Telegram, Feishu (Lark), or enterprise chat bots requiring persistent context.
- Subtask Delegation in Multi-Agent Stacks: Primary coding or research agents can offload long-running background investigations to Dots, retrieving finished deliverables without burning external API balances.
Concurrency and Operational Caveats
While dot2api establishes a viable bridge for developer workflows, production use involves distinct operational constraints that engineers must weigh.
- Lack of Request Concurrency: Dots does not support concurrent requests and queues incoming tasks sequentially, introducing noticeable response delays.
- Idle Session Sleep and Latency: Extended periods of inactivity may cause the cloud environment to enter a low-power standby state, resulting in cold-start delays on initial calls.
- Unofficial Routing and Policy Risks: High-frequency automated calls run the risk of triggering OpenAI's traffic analysis and rate limits, potentially leading to session throttling or administrative scrutiny on non-standard integration paths.
- Promotional Tier Volatility: The zero-quota conversational policy and free cloud resources currently allocated to Dots remain subject to OpenAI's evolving terms of service and could be restricted or monetized in future platform revisions.