Literature Memory
This Literature Management MCP server, developed by an unnamed creator, provides a comprehensive system for managing academic sources and integrating them with knowledge graphs. Built with Python using FastMCP and SQLite, it offers tools for source tracking, note-taking, and entity linking across various source types like papers, books, and webpages. The server implements features such as flexible identifier management, structured note organization, and bidirectional entity relationships. By bridging literature management with knowledge graphs, it enables AI systems to efficiently analyze and contextualize academic sources. This implementation is particularly valuable for researchers and knowledge workers, facilitating use cases such as literature reviews, citation network analysis, and knowledge base construction in academic and professional settings.
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 2026-09-02.
Scan details: Circle-IR · 2026-09-02 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- database
- Source
- PulseMCP
- Author type
- human
- Last scanned
- 2026-09-02
- Updated
- 2026-09-02
Use via MCP
Resolve Literature Memory 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.