Working with an AI

carrel mcp serves the library over the Model Context Protocol, so assistants such as Claude can search it, read papers and figures, follow citations and propose summaries, keywords and notes.

Connecting

Claude Code:

claude mcp add --scope user carrel -- carrel mcp

Claude Desktop, and other clients configured with JSON:

{ "mcpServers": { "carrel": { "command": "carrel", "args": ["mcp"] } } }

Clients that don’t pass your shell’s environment on need settings in carrel’s config file rather than in environment variables.

How an assistant reads a paper

The server tells the assistant to search, then get_paper (metadata, abstract, approved summary and keywords, figure list), and only then read_paper, which returns the full text in chunks so long papers don’t flood its context. Figures come as images (get_figure), supplementary text through read_paper’s file option. The MCP tools page lists everything.

Drafts: the AI proposes, you decide

Everything an assistant writes (a summary, keywords, notes) becomes a draft in the paper’s drafts/ folder; nothing changes in your library until you approve it:

carrel drafts
carrel approve ho2020denoising summary             # replaces the summary
carrel approve ho2020denoising keywords            # replaces the .bib's keywords
carrel approve ho2020denoising notes               # appended to your notes
carrel reject ho2020denoising summary

In the TUI, d shows each draft next to the current version: a approves, r rejects, e edits it first.

Things to ask

• “Read the papers in my thesis project that have no summary yet and propose summaries and keywords.”
• “Which papers cited by ho2020denoising am I missing?”
• “Find what my library says about classifier-free guidance, with page references.”
• “Write the related-work paragraph for these five papers and give me their BibTeX.”