TWI (Text-to-Image)
A text-to-image MCP server implementation that integrates with machine learning models through the transformers library to provide AI-powered image generation capabilities. Built with Python 3.13 and leveraging numpy, Pillow, and Pydantic for robust image processing and data validation, it exposes text-to-image functionality through MCP tools while maintaining clean separation between client and server components. The implementation includes dedicated client testing utilities and follows standard MCP patterns with console script entry points, making it useful for applications requiring image generation from text prompts, AI-assisted creative workflows, and integration of image synthesis capabilities into larger systems.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- media
- Source
- PulseMCP
- Repository
- github.com/bigosprite/mcp-python-twi
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve TWI (Text-to-Image) from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.