Launched March 17, 2026
Scryer
Give your AI agent a blueprint, not a prayer
FreeAIVisual editingAI Agents2,647 impressions#5 of its week1 comment
AI agents can write code, but what you describe and what gets implemented tends to drift. Scryer gives you a shared visual model: you edit it in a drag-and-drop editor, the agent reads and modifies it through MCP. Once the model looks right, the agent generates code from it — get_task feeds work one unit at a time with dependency ordering, inherited contracts, and progress tracking.
Scryer provides a visual drag-and-drop model that AI agents read, edit via MCP, and generate code from.
- for
- Developers building AI-agent-driven code generation pipelines
- pricing
- open source
- license
- open source
Key features
6 features of Scryer
- Drag-and-drop editor — Create and edit a shared visual model that agents can read and modify.
- MCP integration — Agents communicate with the model through a Multi-Channel Protocol server.
- Task feeding — Feed work units one at a time with automatic dependency ordering.
- Inherited contracts — Define and enforce contracts that propagate through generated code.
- Progress tracking — Monitor agent progress and status throughout the generation process.
- Change ledger — Record rationale and changes for each edit made by the agent.
Use cases
- Iteratively design UI layouts and have an AI agent generate the corresponding code
- Define complex data pipelines visually and let the agent produce implementation scripts
- Track and audit AI-generated changes with a built-in change ledger
- Enforce contracts and dependencies when generating multi-module projects
Scryer vs alternatives
 Scryer |  Fine |  SuperAGI Cloud |  Pipelex |  Kubiya.ai | |
|---|---|---|---|---|---|
| Best for | Visual model for AI agents | AI-agent software construction | Managed autonomous AI agents | Declarative AI workflow language | Chat-based DevOps automation |
| Pricing | Open source | Free | Free | Free | Subscription |
| DevHunt upvotes | 5 | 75 | 43 | 40 | 37 |
| Launched | Mar 2026 | Jan 2023 | Jan 2023 | Oct 2025 | Jan 2023 |
- Scryer vs Fine: Fine focuses on building software with AI agents but lacks a visual drag-and-drop model layer.
- Scryer vs SuperAGI Cloud: SuperAGI Cloud runs autonomous agents in the cloud, while Scryer provides a local visual model for agents to edit.
- Scryer vs Pipelex: Pipelex offers a declarative language for AI workflows, whereas Scryer centers on a visual model interface.
- Scryer vs Kubiya.ai: Kubiya.ai provides a ChatGPT-style interface for DevOps tasks, not a visual model for code generation.
Scryer FAQ
What is MCP?+
MCP stands for Multi-Channel Protocol, the communication layer Scryer uses for agents to read and modify the visual model.
Do I need to run a server?+
Yes, Scryer includes an MCP server that agents connect to during code generation.
Can I use Scryer with any LLM?+
Scryer is language-model agnostic; any agent that can communicate via MCP can be used.
Is the visual model stored persistently?+
The model is kept in memory during a session and can be saved or exported by the user.
Summarized by DevHunt from github.com · Sep 27, 2026. Details may change; check the official site.
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