Both Claude and ChatGPT now support MCP – the Model Context Protocol that lets AI apps connect to external tools and data sources. But they implement it differently, wrap it in different interfaces, and target different users. This is a direct comparison of how each app handles extensibility in March 2026.
MCP Support: Both In, Different Approaches
MCP has become the standard protocol for connecting AI assistants to external systems. Both platforms support it, but Claude treats MCP as a first-class citizen while ChatGPT bolted it on alongside an existing plugin architecture.
Claude: Connectors
Claude calls its MCP integrations “Connectors.” There are two types:
Verified Connectors – pre-built, one-click integrations available in a directory of 50+ services. Gmail, Slack, Notion, Asana, Figma, Canva, Jira, and more. Browse them at Settings > Connectors, click enable, authenticate, done. Available on all plans including Free.
Custom Connectors – point Claude at any remote MCP server URL. Supports Streamable HTTP and SSE transports with optional OAuth authentication (Client ID + Secret). This is how developers and companies connect Claude to their own internal systems. Available on Pro ($20/mo) and above.
For local MCP servers (running on your machine), Claude Desktop uses claude_desktop_config.json – a JSON file where you configure stdio-based MCP servers. Claude Code (the CLI) uses .mcp.json project files or ~/.claude.json for global configuration.
MCP Apps – launched January 2026, these extend MCP to deliver interactive UI directly inside Claude’s chat window. Amplitude renders analytics charts inline. Asana turns conversations into project timelines. Slack lets you draft and send messages without leaving Claude. Launch partners include Amplitude, Asana, Box, Canva, Clay, Figma, Hex, Monday.com, and Slack. Available on all plans.
Desktop Extensions – one-click .mcpb packages that install local MCP servers without touching config files. Lower barrier for non-technical users.
ChatGPT: Apps (formerly Connectors)
ChatGPT’s MCP journey went through three phases:
Plugins (dead) – launched 2023, fully deprecated by April 2024. Gone.
GPTs with Actions – replaced plugins. Custom GPTs can call external APIs through “Actions” (OpenAPI spec-based). Still active through the GPT Store. This is not MCP – it is a proprietary extension mechanism.
Apps (MCP) – the current system, built on MCP. Rolled out in beta through Developer Mode. Supports Streamable HTTP and SSE transports with OAuth. OpenAI calls full MCP mode “powerful but dangerous” and warns about prompt injection risks.
Access path: Settings > Connectors > Advanced > Developer Mode. Every tool call shows an expandable JSON payload for inspection, and ChatGPT prompts users to review and approve write operations before execution.
ChatGPT’s MCP works in both Chat mode and Deep Research mode. The Responses API also supports remote MCP servers for programmatic access.
Plan availability: MCP/Apps require Plus ($20/mo) or above. Free and Go ($8/mo) plans do not include MCP support.
The Difference
Claude’s MCP implementation is native – the protocol was created by Anthropic, and the entire app is designed around it. MCP Apps with interactive UI go beyond what the protocol originally specified, turning Claude into a platform where external services render their own interfaces inside the conversation.
ChatGPT’s MCP implementation is additive – it sits alongside GPTs and Actions, which remain the primary extension mechanism for most users. The “Developer Mode” label signals that MCP is still positioned as a power-user feature, not the default experience.
Skills vs GPTs: Two Models for Reusable Intelligence
This is where the platforms diverge most sharply.
Claude: Skills
Skills are instruction files – SKILL.md with YAML frontmatter and markdown body – that teach Claude how to perform specific tasks well. They encode workflows, best practices, reference files, and step-by-step processes.
How they work:
- A skill file defines a name, description, trigger conditions, required tools, reference files, and a detailed process
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Skills can be user-invocable (triggered with
/skill-name) or auto-triggered based on context - Skills reference other files in the project (style guides, templates, API docs) and Claude follows them during execution
- The same SKILL.md files work across Claude Code, Cursor, Gemini CLI, Codex CLI, and other MCP-compatible tools
The ecosystem: Over 334 community-contributed skills as of March 2026. Top skills by installs include find-skills (418K installs), vercel-react-best-practices (176K), and web-design-guidelines (137K).
Skills 2.0 added built-in evaluation – define criteria, run parallel tests, get scored results. You can A/B test skills against each other, measure token usage vs quality, and iterate based on graded reports rather than guesswork.
What skills are not: Skills are not apps. They don’t have their own UI, their own model, or their own conversation. They are instructions that make Claude better at specific tasks within your existing workflow.
ChatGPT: GPTs
GPTs are custom AI assistants – each one is a packaged combination of instructions, knowledge files, and tool access (Actions, Code Interpreter, DALL-E, web browsing).
How they work:
- Create a GPT with custom instructions and optionally upload knowledge files
- Add Actions (API calls to external services via OpenAPI specs)
- Enable built-in tools: Code Interpreter, DALL-E image generation, web browsing
- Publish to the GPT Store for others to discover and use
- GPTs run in their own conversation – you switch to a GPT, interact with it, then switch back
The ecosystem: The GPT Store has thousands of community-created GPTs spanning every category – writing, coding, research, image generation, data analysis, education, and more.
What GPTs are not: GPTs are not composable. You cannot stack multiple GPTs in one conversation. You cannot use a GPT as a step in a larger workflow. Each GPT is its own isolated assistant with its own context.
The Fundamental Difference
Skills modify how Claude works. GPTs replace what ChatGPT is.
A skill says: “When the user asks to write a partnership analysis, follow this process, use these reference files, and structure the output this way.” Claude remains Claude – it just executes this particular task better.
A GPT says: “I am a separate assistant called MarketingBot. I have these instructions and these API connections. Talk to me instead of ChatGPT.”
Skills compose. You can have a code-review skill, a documentation skill, and a deployment skill all active in the same project. Claude applies whichever is relevant to the current task. GPTs don’t compose – you talk to one GPT at a time.
Skills are portable. The same SKILL.md file works in Claude Code, Cursor, Gemini CLI, and any tool that reads the format. GPTs are locked to ChatGPT.
Skills are version-controlled. They live in your project repository alongside your code. GPTs are stored in OpenAI’s cloud.
Feature Comparison
| Feature | Claude App | ChatGPT App |
|---|---|---|
| MCP support | Native, first-class | Beta, Developer Mode |
| Verified integrations | 50+ Connectors | Apps (growing) |
| Custom MCP servers | Yes (Pro+) | Yes (Plus+) |
| Interactive UI from tools | MCP Apps (all plans) | Limited |
| Local MCP servers | Yes (stdio via config) | Yes (Desktop app) |
| Extension marketplace | Skills directory (334+) | GPT Store (thousands) |
| Extension model | Skills (instruction files) | GPTs (custom assistants) |
| Composability | Multiple skills per project | One GPT per conversation |
| Portability | Cross-platform SKILL.md | ChatGPT only |
| Version control | Git-friendly files | Cloud-hosted |
| Built-in eval/testing | Skills 2.0 evals | No |
| Code execution | Claude Code (agentic) | Code Interpreter (sandbox) |
| Image generation | No native generation | DALL-E built-in |
| Context window | 200K tokens | 128K tokens |
| Agentic file editing | Yes (Claude Code) | No |
| OAuth for connectors | Yes | Yes |
| Free tier MCP | Verified connectors + MCP Apps | No MCP on Free |
Pricing Comparison
| Claude | ChatGPT | |
|---|---|---|
| Free | $0 – verified connectors, MCP Apps | $0 – no MCP, limited GPTs |
| Entry paid | Pro $20/mo – custom connectors | Go $8/mo – no MCP; Plus $20/mo – MCP |
| Power user | Max $100-200/mo – 5x-20x usage | Pro $200/mo – unlimited |
| Team | $25-30/user/mo | $25-30/user/mo |
| Enterprise | Custom | Custom |
At the $20/mo tier, Claude gives you custom MCP connectors and MCP Apps with interactive UI. ChatGPT Plus at $20/mo gives you MCP in Developer Mode plus GPT Store access and DALL-E.
ChatGPT’s Pro tier at $200/mo is positioned as unlimited access to the most capable model. Claude’s Max tier at $100-200/mo offers 5x-20x the Pro usage limits.
Code Execution: Different Philosophies
Claude Code is an agentic coding tool. It reads your files, edits them, runs terminal commands, manages git, creates PRs, runs tests, and operates directly on your real codebase. It is a software engineering partner that works in your actual development environment.
ChatGPT Code Interpreter runs Python in a sandboxed environment. Upload a file, write code to process it, download the result. It cannot touch your local files, run terminal commands, or interact with your development environment. It is a data analysis tool, not a coding partner.
For developers, this is the widest gap between the platforms. Claude Code with MCP servers can connect to your databases, APIs, CI/CD pipelines, and project management tools – then write code, run tests, and commit changes. ChatGPT’s coding capabilities are confined to a sandbox.
Where Each Wins
Claude wins on:
- Developer workflows – Claude Code is unmatched for software engineering
- MCP depth – native protocol support, interactive MCP Apps, Desktop Extensions
- Composable extensibility – skills stack, compose, and version-control naturally
- Agentic capability – subagents, parallel execution, worktree isolation, hooks
- Context window – 200K tokens vs 128K
- Free tier connectors – verified connectors and MCP Apps on Free
ChatGPT wins on:
- Ecosystem breadth – GPT Store has thousands of ready-made assistants
- Image generation – DALL-E built-in, no workaround needed
- Non-developer accessibility – GPTs are easier to create than skills for non-technical users
- Brand recognition – larger user base means more community content and tutorials
- Multimodal output – image generation, voice mode, and video understanding
The Strategic Picture
MCP is the standard. Both platforms support it. This means any MCP server you build works with both Claude and ChatGPT – and with Cursor, Gemini, Copilot, and every other tool that implements the protocol.
The real competition is not about MCP support – it is about what each platform does with the connections. Claude is building a platform where external tools become native capabilities through MCP Apps and where domain knowledge is encoded in portable, composable skills. ChatGPT is building a marketplace where custom assistants (GPTs) serve specific use cases and where MCP adds developer-grade extensibility on top.
For developers and technical teams, Claude’s model is more powerful. Skills compose, version-control, and travel between tools. MCP is the foundation, not an afterthought. Claude Code turns the AI from an advisor into a collaborator that operates in your actual environment.
For general users and organizations that want ready-made solutions, ChatGPT’s GPT Store offers more immediate value. Find a GPT, click use, done. No config files, no SKILL.md, no terminal.
The choice comes down to how you work. If you build software and want an AI that works inside your workflow, Claude. If you want an AI that provides packaged solutions you can use immediately, ChatGPT. Both platforms are capable. The architecture of extensibility is what separates them.