I Am the Reason OpenAI Is Killing Unlimited Chats
TL;DR Highlight
Connecting local MCP tools to regular ChatGPT chats gave a parallel coding-agent pool without Codex limits
Who Should Read
A developer who wants to run parallel coding agents on a ChatGPT subscription while saving Codex limits
Core Mechanics
- Local tools wired into regular ChatGPT chats
- A custom MCP server plus OpenAI's Secure MCP Tunnel exposed tools on the author's own machine to ordinary conversations.
- No custom cloud infrastructure was needed.
- Desktop Commander plus CUA
- Desktop Commander handled file access, reading and writing code, terminal commands, tests, and process management.
- CUA (Computer Use Agent) handled screenshots, mouse actions, and testing browser or desktop apps.
- No extra API cost
- The setup used open-source tools, OpenAI's tunnel, the existing ChatGPT subscription, and computers already owned.
- The tunnel and MCP integrations needed no separate paid API inference calls.
- One planner, many workers
- A stronger reasoning model made the plan and split it into GitHub issues.
- Each issue carried context, requirements, and acceptance criteria so another agent could pick it up independently.
- Separate ChatGPT conversations (Sol 6 High) each got one issue.
- GitHub issues as the task queue
- Workers read the project, edited files, ran tests, and iterated through MCP.
- Sharing a filesystem required coordination, and a stronger model occasionally had to step in.
- Unlimited chats end, so the author moves to Claude
- OpenAI announced it is ending unlimited chats and merging them with Codex usage.
- The author says Claude Opus is smarter for their use cases and gives more mileage per subscription, so they are switching.
Community Reactions
- Criticism that people exploiting unlimited plans ruin it for everyone
- It was a reaction to the author's claim that no rules were broken.
- Opinion that the limit change stems from OpenAI's funding troubles
- The view is that OpenAI is becoming more capital-efficient.
- The point is that it likely has nothing to do with this post.
- Experience that Claude's default limits are more generous
- The commenter said using Sol for everything burned through limits.
- Opinion that multi-agent is mostly dead
- The claim is that one big agent loop beats setups like this.
- The commenter only uses sub-agents to compress context, such as tests needing 100+ tool calls.
- They noted multi-agent schemes can bloat token usage by orders of magnitude.
- Experience that a $20 OpenAI sub with your preferred coding agent is a good deal
- It came with the question of whether a Claude sub forces you to use Claude Code.
How to Apply
- Add acceptance criteria to your issue template
- Split one task for AI into a GitHub issue today.
- Fill in context, requirements, and acceptance criteria so another agent can pick it up independently.
- Separate planner and worker roles
- Use the strongest model only for planning and issue breakdown on large features.
- Give implementation to a cheaper model per issue, and reserve the strong one for design and review.
- Prevent file conflicts between parallel workers
- State the file scope each issue may touch.
- On a shared filesystem, use one branch per issue to coordinate.
- Build a tool-call log dashboard for MCP
- Log file reads and command executions in your local MCP gateway.
- Make failures inspectable so you can trace which calls go wrong.
Try It
# Paste into a Claude or ChatGPT chat (simplified version of the author's method: plan → issue breakdown)
You are a senior architect. Split the development task below into a list of GitHub issues that another AI agent can handle independently.
Task: {{development task description}}
Project structure: {{directories / tech stack}}
Each issue must include:
- Title
- Context (why it is needed)
- Requirements
- Acceptance criteria (in testable form)
- File scope to modify
Flag issues whose files overlap, and separate issues that can run in parallel from those that need ordering.
Next step: paste one issue at a time into a new chat and run them as workers.Terminology
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