Qiniu Cloud Storage
Qiniu MCP Server provides a bridge to Qiniu Cloud's storage and media processing services through a Model Context Protocol interface. This Python implementation exposes tools for managing object storage (listing buckets, retrieving files), CDN operations (prefetching, refreshing), and image processing capabilities (scaling, rounding corners, retrieving metadata). The server supports both stdio and SSE transport methods, authenticates via Qiniu access keys configured through environment variables, and includes resource providers that allow AI assistants to browse and access files stored in Qiniu buckets. It's particularly useful for applications that need to manage cloud storage assets or perform on-the-fly image transformations within conversational AI workflows.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately.
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- media
- Source
- PulseMCP
- Repository
- github.com/qiniu/qiniu-mcp-server
- Author type
- human
- Updated
- 2026-04-25
Use via MCP
Resolve Qiniu Cloud Storage 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.