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AI tools for crypto workflows: Codex, GPT, Claude, Gemini, and DeepSeek
A source-led way to separate model, product, host, tools, and approval flow when comparing AI workflows.
“Which AI should I use?” is too broad to answer from a model name. First identify the job, then separate the model family from the application, host, tools, and approval path around it.
Four layers that are easy to mix up
The model generates or interprets text. The product is the application where you interact with it. A coding environment adds files, commands, or an editor. A host or API integration decides which tools and data are actually connected. Two products can expose the same model with different context and permissions.
That is why a model comparison should start with a task:
| Task | Evidence to compare |
|---|---|
| Explain a supplied quote | Context handling, arithmetic transparency, source discipline |
| Edit a codebase | File access, edit controls, validation workflow |
| Read a public service record | Tool schema, endpoint, response states, timestamps |
| Propose a wallet action | Review boundary and whether signing remains explicit |
No model name alone proves that a host supports any one of these paths.
What the official interfaces establish
OpenAI’s function-calling guide describes a model returning a tool call, the application executing it, and a later response using the tool output. Anthropic’s tool-use guide makes the same client-tool boundary explicit: Claude returns a structured call, while client code runs the function and returns a result. Google’s Gemini function-calling guide says the application is responsible for executing the function. DeepSeek’s Tool Calls guide likewise says the functionality must be provided by the user.
These are interface facts, not a ranking. They give you a fair comparison question: where does the function run, what schema does it accept, how is an error returned, and who must approve a side effect?
MCP adds another layer. The MCP TypeScript SDK describes an open standard in which a server exposes tools, resources, and prompts and a host connects to it. A model provider can be one part of that host, but provider support, account access, and a particular connector still need their own documentation check.
Compare the host you are actually using
Codex is a product surface with documented developer interfaces around the model. The official Codex command reference describes CLI commands, file context, shell commands, and a desktop app handoff; the Codex MCP guide documents MCP connections shared by the desktop app, CLI, and IDE extension. The ChatGPT guide describes Chat, Work, and Codex as different ways to work. Those facts describe a host and its permissions, not a guarantee that every model endpoint or local tool is available in every surface.
An API integration is a different boundary. With OpenAI, Claude, Gemini, or DeepSeek function calling, the model can return structured arguments, but the application receives them, validates them, executes its own function, and sends back the result. Claude Code is a separate coding host with its own MCP connection guide; the Claude API tool-use guide describes the API-level client loop. Gemini and DeepSeek likewise document application-executed functions. Compare the configured host and its evidence instead of treating a provider name as an integration claim.
A practical test matrix
Give each candidate the same redacted quote and ask for the same output: define every field, show arithmetic, identify missing data, and state what must be checked in the wallet. For tool use, expose one harmless read-only function with a small schema. Record whether the host shows the tool name, arguments, returned source, and timestamp. If the tool is unavailable, record that instead of silently switching to a guess.
For coding tools, use a disposable file and ask for a small change plus a syntax check. The result measures the workflow you configured, not an abstract “best model.” Do not compare current price, availability, or model quality unless you have a dated primary source and a defined task.
Apply the boundary to a crypto workflow
The participant kit offers six tools total: five bounded read-only tools and one review-only action planner. A host may expose them to ChatGPT, Claude, Gemini, DeepSeek, or another compatible application, but the kit does not assume native support from a model name. Read the MCP connection guide and confirm the host’s current integration instructions.
For a swap, the useful comparison is whether each setup helps you inspect assets, quote fields, and service readback while leaving wallet signing to you. A model that writes a polished answer has not signed a transaction. A tool call that returns a plan has not created Points. Keep those facts in the test notes.