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MCP server · RAG

Chiken

💡✨ Zotero, RAG, MCP, and deep research

44Fair

Scored 6 months ago · breakdown

About Chiken

Chiken is an MCP server in the RAG category: 💡✨ Zotero, RAG, MCP, and deep research.

Install

From source
git clone https://github.com/yuanjua/chiken

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Ask AI

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Security checks

  • ✓README presentThe repository ships documentation.

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README

ChiKen

ChiKen is your private, AI-powered research assistant that transforms your Zotero library into an interactive knowledge base.

✨ Features

ChiKen connects your Zotero library to LLM clients like Claude Desktop through RAG and MCP. Just make a few clicks, your AI clients are ready to search over your documents.

ChiKen chat interface offers three agents to interact with your research: Chat for conversational Q&A with your documents, Search for searching papers online, and Deep Research for comprehensive multi-source investigations that combine your personal library with web search to generate detailed research reports.

https://github.com/user-attachments/assets/983e3e05-6f37-46ba-a19e-69f7207c4e83

💫 Quick Start

Download and install ChiKen from Releases for your platform. PDF and plain text work out of the box; other formats require Pandoc 2+. Zotero 7+ is also required for enabling local API.

We recommend Ollama for local LLMs—easy setup for chat and embeddings. Works well with ollama/gemma3:27b. For now this is the only recommended and tested model. You can then expose your knowledge bases to advanced LLM clients like Claude Desktop through the built-in MCP server.

All data stays local. API keys are stored in your OS keychain:❓You may see prompts asking for keyring access; knowledge bases live on your disk.

For more detailed instructions, see:

Get Started

🗺️ What's Next

ChiKen continues to evolve with enhanced document parsing (both lightweight and powerful options for literature), expanded MCP tools for deeper knowledge interaction, and architectural improvements including a planned shift to PyTauri for better performance.

🌱 Contributing

We’re excited to welcome contributions!
A dedicated section with contribution guidelines and instructions is coming soon.
If you have feature requests, bug reports, or ideas, feel free to open an issue or discussion in the meantime.

💬 The Name

In the world of research, Zotero helps us to see and collect knowledge. The name comes from the Albanian word zotëroj, meaning "to master." But how do we turn that collection into true understanding?

This is the question that inspired ChiKen (知見). The name comes from jñāna-darśana (ज्ञानदर्शन), a Buddhist term for "knowledge and insight." It represents the flash of understanding that comes from deep engagement with information.

ChiKen is designed to complete the journey Zotero begins: the mastery of information (Zotero) and the spark of insight (ChiKen). We want to help you not just collect knowledge, but to connect with it, question it, and ultimately, to see it in a new light.

ChiKen idea

License

The code is licensed under the MIT License. The logo is licensed under CC BY 4.0.

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Chiken

How do I install Chiken?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Chiken safe to use with an AI agent?

Its trust score is 44 out of 100 (fair). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Chiken still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.