Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"io-github-gokmengokhan-endnote-mcp": {
"args": [
"endnote-mcp"
],
"command": "uvx"
}
}
}Are you the author?
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Connect your EndNote reference library to Claude AI. Search references, read PDFs, format citations, find related papers, and generate bibliographies — all directly in Claude Desktop conversations.
Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.
uvx 'endnote-mcp' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
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Checked endnote-mcp against OSV.dev.
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Connect your EndNote reference library to Claude AI. Search references, read PDFs, format citations, find related papers, and generate bibliographies — all directly in Claude Desktop conversations.
Once set up, you can ask Claude things like:
Claude searches your local library — nothing is uploaded to the cloud beyond the normal conversation.
EndNote Library → XML Export → endnote-mcp index → SQLite Database (FTS5 + Embeddings)
↕
Claude Desktop ← MCP Server (12 tools)
Your references and PDF text are indexed into a local SQLite database with full-text search. Optionally, AI embeddings enable semantic search — finding papers by meaning, not just keywords. When semantic dependencies are installed, new references are automatically embedded during indexing. Claude connects through the Model Context Protocol (MCP).
# With uv (recommended)
uv tool install endnote-mcp
# Or with pip
pip install endnote-mcp
In EndNote: File → Export → choose XML format → save to a convenient location (e.g., Desktop).
endnote-mcp setup
The wizard will:
Quit and reopen Claude Desktop. You'll see "EndNote Library" in your MCP connectors.
That's it. Start asking Claude about your references.
Enable meaning-based search that finds references even when they use different terminology than your query. For example, searching "how companies prepare for uncertain futures" finds papers on scenario planning and strategic foresight.
# Install semantic search dependencies
pip install endnote-mcp[semantic]
# Generate embeddings (~3 min for 4,000 references)
endnote-mcp embed
This uses the lightweight all-MiniLM-L6-v2 model locally — no API keys needed, everything stays on your machine.
| Command | What It Does |
|---|---|
endnote-mcp setup | Interactive setup wizard |
endnote-mcp index | Re-index after adding new references (incremental) |
endnote-mcp index --full | Full re-index from scratch |
endnote-mcp index --skip-pdfs | Index metadata only (fast, ~1 sec) |
endnote-mcp index --embed | Re-index and generate embeddings |
endnote-mcp embed | Generate semantic search embeddings |
endnote-mcp embed --full | Regenerate all embeddings from scratch |
endnote-mcp status | Show index statistics |
endnote-mcp install | Add to Claude Desktop config |
| `endnote-mc |