openai-docs▌
boshu2/agentops · updated Apr 8, 2026
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Provide authoritative, current guidance from OpenAI developer docs using the developers.openai.com MCP server. Always prioritize the developer docs MCP tools over web.run for OpenAI-related questions. Only if the MCP server is installed and returns no meaningful results should you fall back to web search.
OpenAI Docs
Provide authoritative, current guidance from OpenAI developer docs using the developers.openai.com MCP server. Always prioritize the developer docs MCP tools over web.run for OpenAI-related questions. Only if the MCP server is installed and returns no meaningful results should you fall back to web search.
Quick start
- Use
mcp__openaiDeveloperDocs__search_openai_docsto find the most relevant doc pages. - Use
mcp__openaiDeveloperDocs__fetch_openai_docto pull exact sections and quote/paraphrase accurately. - Use
mcp__openaiDeveloperDocs__list_openai_docsonly when you need to browse or discover pages without a clear query.
OpenAI product snapshots
- Apps SDK: Build ChatGPT apps by providing a web component UI and an MCP server that exposes your app's tools to ChatGPT.
- Responses API: A unified endpoint designed for stateful, multimodal, tool-using interactions in agentic workflows.
- Chat Completions API: Generate a model response from a list of messages comprising a conversation.
- Codex: OpenAI's coding agent for software development that can write, understand, review, and debug code.
- gpt-oss: Open-weight OpenAI reasoning models (gpt-oss-120b and gpt-oss-20b) released under the Apache 2.0 license.
- Realtime API: Build low-latency, multimodal experiences including natural speech-to-speech conversations.
- Agents SDK: A toolkit for building agentic apps where a model can use tools and context, hand off to other agents, stream partial results, and keep a full trace.
If MCP server is missing
If MCP tools fail or no OpenAI docs resources are available:
In Codex:
- Run:
codex mcp add openaiDeveloperDocs --url https://developers.openai.com/mcp - If it fails due to permissions/sandboxing, retry with escalated permissions.
- Ask the user to restart Codex, then re-run doc search/fetch.
In Claude Code:
- Add the MCP server to
~/.claude/settings.jsonunder"mcpServers":{ "mcpServers": { "openaiDeveloperDocs": { "type": "url", "url": "https://developers.openai.com/mcp" } } } - Restart Claude Code, then re-run doc search/fetch.
In other agents: Ask the user to configure the MCP server per their agent's documentation.
Workflow
- Clarify the product scope (Codex, OpenAI API, or ChatGPT Apps SDK) and the task.
- Search docs with a precise query.
- Fetch the best page and the specific section needed (use
anchorwhen possible). - Answer with concise guidance and cite the doc source.
- Provide code snippets only when the docs support them.
Quality rules
- Treat OpenAI docs as the source of truth; avoid speculation.
- Keep quotes short and within policy limits; prefer paraphrase with citations.
- If multiple pages differ, call out the difference and cite both.
- If docs do not cover the user’s need, say so and offer next steps.
Tooling notes
- Always use MCP doc tools before any web search for OpenAI-related questions.
- If the MCP server is installed but returns no meaningful results, then use web search as a fallback.
- When falling back to web search, restrict to official OpenAI domains (developers.openai.com, platform.openai.com) and cite sources.
Examples
OpenAI API Guidance
User says: "How do I use tool calls with the Responses API?"
What happens:
- Search OpenAI docs MCP for "Responses API tools".
- Fetch the most relevant section.
- Return implementation guidance with citations.
Codex Capability Check
User says: "Does Codex support read-only review workflows?"
What happens:
- Query Codex docs via MCP.
- Fetch flag/sandbox references.
- Answer with source-backed guidance and constraints.
Troubleshooting
| Problem | Cause | Solution |
|---|---|---|
| MCP docs search returns nothing | MCP server not installed | Install openaiDeveloperDocs MCP, restart Codex, retry search |
| Results are stale/unclear | Query too broad | Narrow query by product + feature, then fetch exact page section |
| Need citation-ready answer | Source not fetched | Fetch specific doc section before answering |
| Docs do not cover question | Gap in official docs | State gap explicitly and provide safe best-effort guidance |
How to use openai-docs on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add openai-docs
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches openai-docs from GitHub repository boshu2/agentops and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate openai-docs. Access the skill through slash commands (e.g., /openai-docs) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.4★★★★★43 reviews- ★★★★★Pratham Ware· Dec 28, 2024
I recommend openai-docs for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Anika Robinson· Dec 24, 2024
Solid pick for teams standardizing on skills: openai-docs is focused, and the summary matches what you get after install.
- ★★★★★Arya Martinez· Dec 24, 2024
We added openai-docs from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Dhruvi Jain· Dec 4, 2024
openai-docs is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Oshnikdeep· Nov 23, 2024
Keeps context tight: openai-docs is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Emma Malhotra· Nov 15, 2024
openai-docs has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Carlos Sanchez· Nov 15, 2024
Useful defaults in openai-docs — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Ganesh Mohane· Oct 14, 2024
Registry listing for openai-docs matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Dev Sethi· Oct 6, 2024
Useful defaults in openai-docs — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Ishan Ndlovu· Oct 6, 2024
openai-docs has been reliable in day-to-day use. Documentation quality is above average for community skills.
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