Moonshot AI × WorkDaddy: LLM Provider Integration (2026)
Use Moonshot AI as the engine behind your WorkDaddy agent team: 10 models available, context windows up to 1M tokens, connected in minutes with your own key.
Moonshot AI is one of 178 LLM providers supported by WorkDaddy’s model layer in 2026, in the China Model Providers group. The catalog currently lists 10 models from Moonshot AI: 7 with explicit reasoning, 5 with vision input, and 10 with tool calling — the capability that matters most for agent work. The largest context window reaches 1M tokens.
At a glance
| Models available | 10 |
|---|---|
| Reasoning models | 7 |
| Vision models | 5 |
| Tool-calling models | 10 |
| Largest context window | 1M tokens |
| API endpoint | https://api.moonshot.ai/v1 |
| API key variable | MOONSHOT_API_KEY |
| SDK adapter | @ai-sdk/openai-compatible |
| Provider docs | platform.moonshot.ai ↗ |
Why run WorkDaddy agents on Moonshot AI in 2026
Tool calling, context size, and cost decide how well a provider drives an agent team. Moonshot AI brings 10 tool-calling models to WorkDaddy — enough to power the full loop of storefront edits, analytics queries, and content production — with 1M tokens of context at the top end for whole-codebase and long-report work. Because WorkDaddy is model-agnostic, you can route heavy reasoning to Moonshot AI’s strongest model and bulk work to its cheapest, inside one team.
Best Moonshot AI models for e-commerce agents (2026)
The current flagships from Moonshot AI in the WorkDaddy catalog, newest first:
Kimi K3 — Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work (1M context)
Kimi K2.7 Code HighSpeed — Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking (262K context)
Kimi K2.7 Code — Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking (262K context)
Kimi K2.6 — Multimodal Kimi workhorse for agent loops, coding tasks, and visual context (262K context)
Kimi K2.5 — Earlier Kimi frontier model for long-context agents, coding, and multimodal work (262K context)
Kimi K2 Thinking Turbo — Kimi reasoning model for long-horizon research, planning, and tool use (262K context)
How to connect Moonshot AI to WorkDaddy
WorkDaddy talks to Moonshot AI at api.moonshot.ai via the @ai-sdk/openai-compatible adapter. Add your credential (typically MOONSHOT_API_KEY) in Settings → Models, pick a default model, and every agent can use it immediately — or add Moonshot AI as one engine among several and let tasks route to the best fit.
Featured models
| Model | Context | Reasoning | Released |
|---|---|---|---|
| Kimi K3 | 1M | Yes | 2026-07-16 |
| Kimi K2.7 Code HighSpeed | 262K | Yes | 2026-06-12 |
| Kimi K2.7 Code | 262K | Yes | 2026-06-12 |
| Kimi K2.6 | 262K | Yes | 2026-04-21 |
| Kimi K2.5 | 262K | Yes | 2026-01 |
| Kimi K2 Thinking Turbo | 262K | Yes | 2025-11-06 |
How it works
Connect
In WorkDaddy, open Settings → Models, choose Moonshot AI, and paste your API key (MOONSHOT_API_KEY). No key? Start on the managed gateway instead.
Put agents to work
Pick Kimi K3 or any of the 10 available models as your default — per-agent overrides let you match model to task.
Review and approve
Agent output stays draft-first regardless of the model: review diffs and approve actions exactly as before.
Frequently asked questions
Does WorkDaddy support Moonshot AI in 2026?
Yes — Moonshot AI is a supported LLM provider with 10 models in the WorkDaddy catalog, connected with your own API key via the @ai-sdk/openai-compatible adapter.
How many Moonshot AI models can I use with WorkDaddy?
10 models are listed for Moonshot AI, including 7 reasoning models and 5 vision-capable models. The flagship lineup above shows the newest.
What context window do Moonshot AI models offer?
Up to 1M tokens on the largest model — relevant for whole-repo storefront work and long analytics reports.
Is Moonshot AI the best LLM provider for e-commerce agents?
It depends on the task mix — Moonshot AI sits in the China Model Providers group. WorkDaddy is model-agnostic, so the practical answer in 2026 is to combine providers: route each agent task to whichever model fits best.
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Put the team to work on your store
Connect your storefront, analytics, and email stack, set a goal, and let the agents run the work end to end. Start on the free plan with your own model key.