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wenyuchiou avatar

Research Hub

wenyuchiou/research-hub
25STDIOregistry active
Summary

If you run Zotero, Obsidian, and NotebookLM together and want Claude to handle the repetitive pipeline work, this is the glue layer. It exposes MCP tools for searching arXiv and Semantic Scholar, ingesting papers into all three systems, syncing notes, generating AI briefs, and caching canonical answers as structured Markdown crystals. The package includes a live dashboard, a REST API, and per-cluster Obsidian Bases views. It's built for literature workflow automation: the kind where you're tracking seven research clusters and need an agent to run the ingest, verify, and sync steps without copy-pasting between tools. Ships with stdio transport and works without OpenAI keys if you're using NotebookLM for generation.

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research-hub

A local workspace connecting literature, research artifacts, and manuscripts through traceable work.

繁體中文 · Workspace guide · Existing setup · Developer architecture

PyPI Python 3.10+ MIT license

Workspace preview — unmerged and unreleased. The six-page workspace below is proposed in research-hub PR #135. PyPI 1.2.0 does not include it. Use the pinned preview installation below, or try the published literature dashboard.

Why this exists

Research crosses files and tools: a paper informs a question, an analysis changes a result, and a manuscript needs revision. Keep those connections visible when you or an AI assistant picks up the next task.

Concept diagram: research questions connect literature, evidence, analysis, manuscript proposals, and human review; changed inputs return work for review.

Start with local files. Connect Zotero for references, Obsidian for notes, and NotebookLM for source-based briefings when needed. Empirical studies and literature reviews share the workspace.

What you work with

Actual workspace UI running local demo fixtures, showing the project navigation and traceable research records.

PageYour work
ProjectState the question, goal, and project type.
LiteratureFind references and record inclusion or exclusion decisions.
EvidenceConnect claims to sources and inspect unresolved support.
Design & resultsRecord methods, results, limitations, and supporting files.
ManuscriptRegister Word, LaTeX, or Markdown; prepare outlines and revisions.
Review & deliveryInspect proposals, record decisions, and prepare a local handoff.

Files stay in your selected workspace. Registration records paths and hashes; your editor remains responsible for changing original documents.

How to try it

Workspace preview

Use Python 3.10+ and Git. Choose a new or empty workspace-demo directory. These commands install the tested, immutable preview snapshot dda3cee30f43e7eca658bfeb9b20aac35ec19ce8 without depending on a feature-branch name.

git clone -c core.autocrlf=false https://github.com/WenyuChiou/research-hub.git
cd research-hub
git fetch origin dda3cee30f43e7eca658bfeb9b20aac35ec19ce8
git checkout --detach dda3cee30f43e7eca658bfeb9b20aac35ec19ce8
python -m pip install -e '.[mcp]'
research-hub project demo --root ./workspace-demo --json
research-hub serve --workspace --root ./workspace-demo

Open the local workspace. The demo needs no account and contains a small numerical summation example and a literature-review fixture. These are teaching inputs, not model-generated research findings.

The snapshot retains its original documentation; use the current workspace guide for the merged producer pin, your own files, writing setup, task handoffs, and review. See dated verification and remaining checks before relying on the preview.

Published literature dashboard

python -m pip install research-hub-pipeline
research-hub dashboard --sample

This account-free sample opens the existing dashboard. For real integrations, use the setup guide, first 10 minutes, and dashboard tour.

How writing works

Concept diagram: a researcher prepares a task, uses a portable AI handoff or a connected Codex prose worker, checks the proposal, and explicitly accepts or requests changes.

ModeWhat happens
Portable handoffExport a task for your AI host; import its prose and candidate hashes. Export leaves the task waiting for the agent.
Connected CodexAn authenticated, compatible Codex CLI uses an explicitly trusted public writing bundle to produce prose without tools. Results wait for human review.

The public writing adapter was merged in academic-writing-skills PR #17. This integration pins its immutable main commit bc15e29e976cd6ade3484aeaa4f1230444697f8a. Verify and configure it explicitly; it is optional and is not installed as a permanent research-hub dependency. The Hub workspace remains an unmerged, unreleased preview. Connected Codex receives bounded text excerpts, not binary document contents. Use your editor for Word formatting, LaTeX compilation, and final document changes.

What you can trust

  • Traceable inputs: tasks retain input revisions, results, and decisions. Changed registered bytes can make a task stale; the workspace reports review impact.
  • Separate judgments: a resolvable reference does not prove a claim. Source identity, claim support, and human task acceptance remain distinct.
  • Explicit handoff: accepted proposals can enter a separately approved local ZIP. This does not authorize publication or cloud upload.

Local approval records an operator's assertion; it does not authenticate identity on a shared computer. Existing direct-write MCP, dashboard, and cloud tools are outside workspace approval protection. The workflow's eight stages do not advance automatically when a task finishes. Read the boundaries and recovery guide.

Existing integrations, credentials, and troubleshooting

Use setup to choose integrations, then run research-hub doctor. NotebookLM needs a visible Google sign-in; its last recorded authentication attempt failed and has not been reverified. Treat that integration as degraded/unchecked until your own check succeeds. See NotebookLM setup and troubleshooting.

Existing personaOptional extras
Researcher[playwright,secrets]
Humanities[playwright,secrets]
Analyst[import,secrets]
Internal KM[import,secrets]

These credentials apply to the existing integrations; the local workspace demo needs none.

NameRequiredPurpose
ZOTERO_API_KEYZotero onlyZotero API authentication
ZOTERO_LIBRARY_IDZotero onlyZotero library identifier
SEMANTIC_SCHOLAR_API_KEYnoOptional search API key
SEMANTIC_SCHOLAR_RPSnoOptional search request-rate override
TAVILY_API_KEYnoOptional web search backend
BRAVE_API_KEYnoOptional web search backend

Connect through MCP/REST, check the AI host support matrix, or use local file import. The CLI reference, EZproxy guide, and live smoke checklist cover detailed operations.

Developer links

The workspace architecture explains the task ledger and approval boundaries. See the workflow runtime, MCP tools, stable API, file formats, and OpenWiki for technical detail. Use python -m research_hub describe --filter mcp_tools and --filter skills for current inventories.

Earlier dashboard material remains available: MCP flow diagram, recorded dashboard demo, and full-resolution video.

Contributing · Releases · Release process · MIT license

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Categories
Documents & KnowledgeSearch & Web Crawling
Registryactive
Packageresearch-hub-pipeline
TransportSTDIO
UpdatedMay 26, 2026
View on GitHub

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