glama scanned Safe content atomic mcp-remote

shelfmark

Shelfmark is an MCP server that builds a local metadata catalogue of your documents, enabling AI agents to discover, search, and select relevant files without opening or indexing their contents. It provides governed access with ownership and confidentiality controls, ensuring agents only see what they are permitted to.

Cognium trust score

Tier

Scanned

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 2026-08-29.

Scan details: Circle-IR · 2026-08-29 · Appeal

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Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: mcp-remote
Category: ai-ml
Source: Glama
Repository: github.com/Dankaro-projects/shelfmark
Author type: human
Last scanned: 2026-08-29
Updated: 2026-08-29

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MCP

Resolve shelfmark 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

Swap --scope user for --scope project to commit it to .mcp.json.

Your client Same endpoint everywhere; only the config key differs. The full list is in the descriptor.

Claude Desktop · Settings → Connectors → Add custom connector

https://api.skillsregistry.net/mcp

Paste the URL as the connector endpoint. No authentication.

ChatGPT · Settings → Connectors → Create (developer mode) → MCP server URL

https://api.skillsregistry.net/mcp

Authentication: none. Works in chat and deep research — the server exposes the connector search and fetch tools.

Codex CLI · ~/.codex/config.toml

[mcp_servers.skillsregistry]
url = "https://api.skillsregistry.net/mcp"