Image Download and Optimize
This MCP image downloader server, developed by qpd-v, provides tools for downloading and optimizing images through a standardized interface. It leverages libraries like Sharp and Axios to enable AI assistants to retrieve images from URLs and perform basic optimization tasks such as resizing, quality adjustment, and format conversion. Built with TypeScript and following MCP standards, it offers a modular approach to image processing that can be easily integrated into existing AI workflows. The implementation is particularly useful for scenarios requiring programmatic image acquisition and manipulation, such as content generation, data preprocessing for machine learning, or automated web scraping tasks.
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 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · 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/qpd-v/mcp-image-downloader
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
Use via MCP
Resolve Image Download and Optimize 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.