Install
$ agentstack add mcp-ai-ql-chat-ui ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Chat UI
[](https://vuejs.org) [](https://vuetifyjs.com)
[](https://hub.docker.com/repository/docker/aiql/chat-ui/tags?page=1&ordering=last_updated) [](https://github.com/AI-QL/chat-ui/blob/main/LICENSE)
The UI of Chat is becoming increasingly complex, often encompassing an entire front-end project along with deployment solutions.
This repository aims to construct the entire front-end UI using a single HTML file, aiming for a minimalist approach to create a chatbot.
By simplifying the structure and key functions, developers can quickly set up and experiment with a functional chatbot, adhering to a slimmed-down project design philosophy.
Features
- Supports OpenAI-format requests, enabling compatibility with various backends such as
HuggingFace Text Generation Inference (TGI),vLLM, etc.
- Automatically supports multiple response formats without additional configuration, including standard
OpenAIresponse formats,Cloudflare AIresponse formats, andplain textresponses
- Support various
backend endpoints through custom configurations, providing any project with a universal frontend chatbot
- Support the
download of chat history, interrupt the current generation, and repeat the previous generation to quickly test the backend inference capabilities
- Support
MCP (Model Context Protocol)by acting as a renderer and facilitating community interactions with the backend main process via IPC
- Inquiries with image inputs can be made using
multimodal vision models
- Support for toggling between
original formatandMarkdown formatdisplay
- Support internationalization and localization
i18n
How to use
Option 1: Chat with demo AIQL
> The demo will use Llama-3.3-70B-Instruct by default
> Multimodal image upload is only supported for vision models
> MCP tools call necessitates a desktop backend and LLM support in OpenAI format, referencing Chat-MCP
Option 2: Download [Index](./index.html) and open it locally (recommended)
Option 3: Download [Index](./index.html) and deploy it by python
cd /path/to/your/directory
python3 -m http.server 8000
> Then, open your browser and access http://localhost:8000
Option 4: fork this repo and link it to Cloudflare pages
> Demo: https://www2.aiql.com
Option 5: Deploy your own Chatbot by Docker
docker run -p 8080:8080 -d aiql/chat-ui
Option 6: Deploy within Huggingface
> Don't forget add app_port: 8080 in README.md
Option 7: Deploy within [K8s](#k8s-section)
Option 8: Integrated as a renderer within the desktop application
> Demo: Chat-MCP
How to config
By default, the Chatbot will use API format as OpenAI ChatGPT.
You can insert your OpenAI API Key and change the Endpoint in configuration to use API from any other vendors
You can also download the config template from [example](./example/config) and insert your API Key, then use it for quick configuration
Trouble Shooting
If you're experiencing issues opening the page and a simple refresh isn't resolving the issue, please take the following steps:
Reset Interface Configuration
- Click
Refreshicon on the upper right ofInterface Configuration
Reset All Configuration
- Click hidden botton on the right side of the index page
- Click
Reset All Configicon
Reset Cache
- Right-click your browser page and go to the
Networksection. - Right-click on section table and clear your browser's cache and cookies to ensure you have the latest version of the page.
- Additionally, inspect the browser's Network section to see which resources are failing to load due to your location. This will provide you with more specific information about the issue.
K8s
- Introduce the image as sidecar container
```yaml spec: template: metadata: labels: app: my-app spec: containers:
- name: chat-ui
image: aiql/chat-ui ports:
- containerPort: 8080
```
- Add service
```yaml apiVersion: v1 kind: Service metadata: name: chat-ui-service spec: selector: app: my-app ports:
- protocol: TCP
port: 8080 targetPort: 8080 type: LoadBalancer ```
- You can access the port or add other ingress
```yaml apiVersion: networking.k8s.io/v1 kind: Ingress metadata: name: my-app-ingress annotations: nginx.ingress.kubernetes.io/rewrite-target: /$1 spec: rules:
- host: chat-ui.example.com
http: paths:
- path: /
pathType: Prefix backend: service: name: chat-ui-service port: number: 8080 ```
Demo
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: AI-QL
- Source: AI-QL/chat-ui
- License: Apache-2.0
- Homepage: https://chat.aiql.com
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.