Chatluna
Multi-model LLM chat plugin for Koishi with agentic tool calling, MCP, and multimodal output
For Koishi bot builders, ChatLuna is the all-in-one plugin that saves you from juggling multiple single-purpose modules. Its agentic sandbox and MCP integration are standout features, but the Koishi dependency means outsiders should look elsewhere. If you're not on Koishi, consider standalone alternatives like Open WebUI or Jan.
Verified 2d ago · liveness 64/100 · cite: rightaichoice.com/tools/chatluna
- Koishi bot developers building multi-model chatbots
- Users who want a single plugin for diverse LLM backends
- Developers needing agentic capabilities with sandboxing
- Content creators seeking multimodal output in chat
- Non-Koishi users (requires Koishi framework)
- Those needing standalone desktop or mobile apps
- Enterprise teams requiring SLA-backed support
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Skip ChatLuna if you're not building on the Koishi framework, or if you need standalone apps, SLA-backed support, or built-in fine-tuning.
As a free open-source plugin, there are no direct costs, but you must provide your own API keys for each model provider, which may incur usage fees.
ChatLuna is free and open-source, so the only costs are your own API usage fees. Compared to standalone tools like Open WebUI (which is also free but less integrated), or commercial platforms like Poe that require subscriptions, ChatLuna is cost-effective for Koishi users who already pay for API access.
In short
Chatluna — Multi-model LLM chat plugin for Koishi with agentic tool calling, MCP, and multimodal output. Best for Koishi bot developers building multi-model chatbots, Users who want a single plugin for diverse LLM backends, Developers needing agentic capabilities with sandboxing. Free to use.
What people actually say about Chatluna — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
24 mentions across 2 sources (YouTube, Bluesky) · researched Jul 28, 2026.
- +Supports multiple major LLMs: Deepseek, OpenAI, Gemini, Claude.
- +Integrates agentic tool calling with sandboxed execution.
- +MCP (Model Context Protocol) support for advanced workflows.
- +Multimodal input (images) and multi-format output (text, image, voice).
- +Low-code setup via Koishi plugin marketplace.
- −No community feedback exists to validate real-world performance.
- −Requires Koishi framework — not a standalone solution.
- −Setup complexity may be high for non-developer users.
- −Lack of reviews makes it risky to adopt for critical projects.
- −Documentation quality is unverified by users.
- • No hidden costs reported; free as in beer and speech.
Viability Score
How well maintained and how widely used is Chatluna? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: September 2026
How we score →Key Features
- Multi-model integration (Deepseek, OpenAI, Gemini, Claude)
- Agentic tool calling with sandbox execution
- MCP (Model Context Protocol) support
- Web search capability via tools
- Multimodal image input processing
- Multi-format output (text, image, voice)
- Koishi plugin ecosystem integration
- Extensible model adapter architecture
- Community-contributed model platforms
- Low-code configuration via Koishi marketplace
- Tool registration via plugin system
- Custom agent API for developers
About Chatluna
ChatLuna is an open-source plugin for the Koishi chatbot framework that brings multi-platform large language model (LLM) chat services to your bots. It integrates with major AI providers including Deepseek, OpenAI, Google Gemini, and Anthropic Claude, letting you switch between models without rewriting configuration. Designed for both developers and power users, ChatLuna offers extensible architecture for adding new model platforms and tools. It supports complex agentic workflows such as sandboxed tool calling, MCP (Model Context Protocol) integration, and web search. The plugin also handles multimodal inputs (images) and renders output in text, image, or voice formats. Licensed under CC-BY-SA-4.0, it is actively maintained on GitHub with a community-driven development model. Targeted at Koishi users and bot developers, ChatLuna provides a low-code setup through Koishi's plugin marketplace. You can configure multiple model endpoints without writing complex configuration files. Its Agent mode allows LLMs to call arbitrary tools, making it suitable for tasks like code execution, data retrieval, and interactive assistants. The plugin differentiates itself through its focus on extensibility and rendering flexibility while remaining free and open-source. ChatLuna's architecture is modular: each model provider is a separate adapter, and tools are registered via a plugin system. This design enables community contributions and custom integrations. The plugin's rendering pipeline converts model responses into rich outputs (e.g., text with image attachments or speech) via Koishi's messaging framework. For developers, the plugin exposes APIs for creating custom agents and tool integrations. What sets ChatLuna apart is its all-in-one approach within the Koishi ecosystem: it replaces multiple single-purpose plugins by offering chat, tools, and multimodal support in one package. However, it requires Koishi as a host and is not a standalone application.
Behind the Verdict
ChatLuna is a strong choice if you're already building bots on Koishi. Its main strength is consolidation: instead of installing separate plugins for chat, tool calling, and multimodal output, you get one package that handles all three. The modular adapter architecture means you can swap between Deepseek, OpenAI, Gemini, and Claude without rewriting your config, which is a huge time-saver. Agent mode with sandboxed execution and MCP support is genuinely useful for automation tasks, and the rendering flexibility (text, image, voice) sets it apart from simpler chat plugins. However, the tool is useless outside the Koishi ecosystem—if you're not using Koishi, you'll need to look at standalone options like Open WebUI or Jan. There's no official support SLA, and you're relying on community contributions for new model adapters, so platform updates may lag. Also, the CC-BY-SA-4.0 license might be a concern if you want to build a commercial product on top of it. Overall, it's a solid pick for Koishi developers who want comprehensive LLM capabilities, but not for others.
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Real-world workflow fit
Concrete scenarios for the personas Chatluna actually fits — and what changes day-one when you adopt it.
You want to add multi-model chat to your Koishi bot without managing separate plugins.
Outcome: Install ChatLuna from the Koishi marketplace, configure Deepseek as the default model, and enable agent mode with web search—your bot can now answer queries with real-time data.
You need a bot that can execute code in a sandbox and use MCP tools.
Outcome: Set up ChatLuna with the sandbox tool, register a code execution tool, and your bot can perform safe code runs when asked, with responses rendered as text or images.
You want your bot to respond with voice messages in your Discord-like chat channel.
Outcome: Enable TTS output in ChatLuna, and your bot will render text responses as voice messages, making interactions more engaging.
Use Cases
- Build a chatbot that can switch between OpenAI, Gemini, and Claude within Koishi.
- Create an agent that executes code in a sandbox via MCP tools.
- Render LLM responses as voice messages using TTS integration.
- Enable web search for your bot to answer real-time queries.
- Handle image inputs for vision-capable models like Gemini or GPT-4V.
Models Under the Hood
as of 2026-08-28
Limitations
- ChatLuna is a plugin for the Koishi framework, requiring Koishi to be installed and configured.
- Model integration depends on user-provided API keys and the availability of the respective platforms.
- The plugin supports agentic tool calling, MCP, and multimodal output, with capabilities limited by the underlying model's tool-use performance and context window.
as of 2026-08-26
Verification history
We have re-verified Chatluna 7 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 7 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Chatluna tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Open Source (GitHub)
$0
Ideal for
Koishi developers and bot builders who want a free, community-supported plugin with full source code access and the ability to customize or contribute.
What this tier adds
Starting tier: fully free with no paywall, includes all features like multi-model support, agentic tools, and MCP.
Where the pricing makes sense
The company stage and team size where Chatluna's pricing actually pencils out — and where peers do it cheaper.
ChatLuna is free and open-source, so the only costs are your own API usage fees. Compared to standalone tools like Open WebUI (which is also free but less integrated), or commercial platforms like Poe that require subscriptions, ChatLuna is cost-effective for Koishi users who already pay for API access.
Setup time & first value
How long it actually takes to get something useful out of Chatluna — broken out by persona, not the marketing-page minute.
For a Koishi user familiar with the marketplace, you can install and configure ChatLuna in under 30 minutes. If you need to set up API keys and test agentic tools, expect about an hour.
Switching to or from Chatluna
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Single-purpose plugins: Replace separate chat, tool, and TTS plugins with ChatLuna's unified plugin, then configure your models and tools in one place.
- ↗To Standalone platforms: If you leave Koishi, migrate to Open WebUI or Jan, but you'll need to rebuild your agent workflows and integrations.
Integrations
Resources & Guides
Tutorials & Learning
Official links
Tools that pair well with Chatluna
Common stack mates teams adopt alongside Chatluna, with the specific reason each pairing earns its keep.
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