Endnote Mcp

C+ 74 completed
Ai Ml
cli / python · tiny
25
Files
4,011
LOC
1
Frameworks
5
Languages

Pipeline State

completed
Run ID
#301602
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
48.77
Framework unique
Isolation
Last stage change
2026-04-16 18:15:42
Deduplication group #47628
Member of a group with 1 similar repo(s) — canonical #27307 view group →
Top concepts (4)
testingFactorySearchTesting
Citation: Repobility (2026). State of AI-Generated Code. https://repobility.com/research/

AI Prompt

Build me a command-line tool in Python that connects a local EndNote reference library to the Claude AI platform. The tool needs to allow users to search references, read specific pages from associated PDFs, format citations (like APA), generate bibliographies, and export references as BibTeX. It should index the library into a local SQLite database, supporting both keyword and optional semantic search using embeddings. The CLI should guide the user through exporting their EndNote XML and running the setup wizard.
python cli endnote claude sqlite ai citation pdf semantic-search
Generated by gemma4:latest

Catalog Information

This project connects an EndNote reference library to the Claude AI platform for searching, citing, and reading PDFs within conversations.

Description

Endnote-mcp is a tool that enables seamless integration of EndNote libraries with the Claude AI platform. It allows users to search, cite, and read PDFs directly within their conversations. This project leverages Click, Hugging Face, and Rich for its functionality.

الوصف

هذا المشروع يربط مكتبة المراجع في EndNote مع منصة Claude AI لتحقيق البحث والاستشهاد وتحميل الملفات النصية مباشرة داخل المحادثات. يستخدم هذا المشروع Click و Hugging Face و Rich لتنفيذه.

Novelty

7/10

Tags

reference-management citation-integration pdf-search conversation-based-research

Technologies

click huggingface rich

Claude Models

claude-opus-4.6

Quality Score

C+
74.2/100
Structure
89
Code Quality
53
Documentation
65
Testing
85
Practices
76
Security
92
Dependencies
80

Strengths

  • CI/CD pipeline configured (github_actions)
  • Good test coverage (64% test-to-source ratio)
  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected
  • Properly licensed project

Weaknesses

  • 454 duplicate lines detected \u2014 consider DRY refactoring

Security & Health

4.6h
Tech Debt (C)
High
DORA Rating
A
OWASP (100%)
Source: Repobility analyzer · https://repobility.com
PASS
Quality Gate
A
Risk (3)
AGPL-3.0
License
9.6%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
93.9%
markdown
3.4%
toml
1.4%
yaml
0.6%
json
0.6%

Frameworks

pytest

Symbols

function101
variable14
constant4
class2
method1

Concepts (4)

Repobility analysis · methodology at https://repobility.com/research/
CategoryNameDescriptionConfidence
Repobility · open methodology · https://repobility.com/research/
arch_layertestingDetected testing layer70%
design_patternFactoryFound factory/create_ naming patterns60%
business_logicSearchDetected from 5 related files50%
business_logicTestingDetected from 8 related files50%

Quality Timeline

1 quality score recorded.

View File Metrics
All rows scored by the Repobility analyzer (https://repobility.com)

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BinComp Dependency Hardening

All packages →
5 of this repo's dependencies have been scanned for binary hardening. Grade reflects RELRO / stack canary / FORTIFY / PIE coverage.
Nmcp1.27.0 · 0 gadgets · risk 971.5Nclick8.3.2 · 0 gadgets · risk 0.0Flxml6.0.3 · 3,127 gadgets · risk 0.0Fnumpy2.4.4 · 6,596 gadgets · risk 0.0Nrich14.3.4 · 0 gadgets · risk 0.0