Akwadra
Build web apps with your AI and host them on Akwadra.
- Category
- Pending
- Primary Subcategory
- Pending
View in the Claude registryIntegration details
Description
Connect Akwadra to create and edit web-app projects from your AI conversation. Your AI writes the source; Akwadra stores it, checks file structure and JSON syntax, and provides a static HTML preview. Review the project and activate paid hosting from your Akwadra dashboard when ready. Hosted builds run in an isolated Railway project backed by a private GitHub repository. Read build logs through the connector and ask your AI to fix errors. This workflow does not call an Akwadra code-generation model. Your AI provider's subscription and usage limits still apply. Free source workspaces are limited to five projects, 200 text files per project and 2 MB of source per project. Full server execution requires hosting; the free preview supports HTML and inline styles, not JavaScript execution or backend services. External services and AI features inside finished apps have separate costs.
- Integration type
- Connector
- Verification status
Community connector- Platform
- Claude
- Category
- Pending
- Primary Subcategory
- Pending
- Secondary Subcategories
- None listed
- Brand
- Unknown
- Access
- Account required
- First tracked
- 2026-09-22
- Tool count
- 7
- Geography
- US
The broad Category that contains the Primary Subcategory.
The Primary Subcategory used for this profile’s headline score.
Other Subcategories where the Integration is listed.
Claude Discoverability Score
Claude Connector discovery is coming soon
Community Connectors only appear in Claude’s registry.Once verified, organic discovery begins and we can calculate your score.Read more about Community Connector verification.
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What discovery looks like
Claude can surface verified Connectors when they match a user’s Prompt.
How Claude Connector discovery works
Your Connector will compete to appear for users’ Prompts once Claude verifies it
Competitive lineup
7 tools agents can invoke
How do I improve a Community connector's discoverability?
The levers are the listing surface agents actually read: names, descriptions, keywords, tool metadata, and registry health. Which lever matters depends on where discovery breaks, which is what continuous measurement shows.
Where is this profile measured?
This profile uses the geography attached to the latest public registry snapshot: US. Locale tags are intentionally omitted.