Research Hub
io.github.WenyuChiouPublished by GitHub account WenyuChiouv1.0.0Updated Oct 24, 2026
Research workspace for Zotero + Obsidian + NotebookLM. Search, ingest, sync, verify briefs.
Overview
A local research workspace MCP server that connects Zotero references, Obsidian notes and NotebookLM briefings to traceable project, evidence and manuscript led
- What you can do
- Organize research projects: state the question, goal and project type, and track tasks with input revisions and decisions across the workflow stages. Manage literature: find references, record inclusion or exclusion decisions, and register Word, LaTeX or Markdown manuscripts. Link evidence: connect claims to sources and inspect unresolved support. Record design and results: methods, results, limitations and supporting files. Handle review and handoff: inspect proposals, record decisions, and export accepted work as a local ZIP. Optionally hand writing tasks to an AI host or a connected Codex CLI for prose, with results waiting for human review.
- When to use it
- Useful for researchers and analysts who keep literature in Zotero, notes in Obsidian and briefings in NotebookLM and want an assistant to keep the links between sources, claims and manuscripts visible. Suited to empirical studies and literature reviews that need traceable inputs and explicit human approval.
- Requirements
- Runs locally over stdio as the PyPI package research-hub-pipeline; the workspace preview needs Python 3.10+ and Git and an empty workspace directory. The demo needs no account. Real integrations may use ZOTERO_API_KEY and ZOTERO_LIBRARY_ID, plus optional SEMANTIC_SCHOLAR_API_KEY, TAVILY_API_KEY and BRAVE_API_KEY. NotebookLM needs a visible Google sign-in.
Installation
In SourceWeft
- Open Research Hub in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
research-hub
A workspace on your computer for researchers to organize papers, evidence, and drafts, with AI-assisted proposals you review.
繁體中文 · Workspace guide · Setup guide · Developer architecture
[PyPI] [Python 3.10+] [MIT license]
Why research-hub?
Research is spread across papers, notes, analysis, and manuscripts. A new paper can change a question; an updated file can make a conclusion or section worth revisiting. research-hub gives researchers and AI assistants a local workspace to record those connections, hand off tasks, and review proposals before accepting them.
- Keep context: bring questions, sources, evidence, results, and manuscripts into one project rather than leaving them only in a conversation.
- Track changes: register file paths and a file fingerprint (hash) to help detect changes, then inspect work that may need review when inputs change.
- Keep decisions human: AI proposals require review; a local delivery requires separate approval.
Install and get started
Try the local workspace
Start with the workspace below. If you only want to try the older published literature dashboard, see the separate option below.
You need Python 3.10+ and Git. These commands install a specific source revision and create teaching fixtures in a new or empty workspace-demo directory. The source workspace is separate from the PyPI release: a package version does not establish that the installed wheel contains current source features.
Choose the block for your system. They call the virtual environment's Python directly, without activation or changing PowerShell execution policy. Dependency installation needs network access.
macOS / Linux
Windows PowerShell
One Windows test environment using the earlier 14ddc070 source encountered WinError 5 during demo creation; its cause is not yet known. See verification and environment notes.
Open http://127.0.0.1:8765/app/. The demo contains two teaching projects. In the Projects dropdown, choose DEMO: three floating-point summation cases (summation-demo) or DEMO: floating-point reading and review outline (review-demo), then open Literature to see the literature page. These are teaching inputs, not research findings, and need no account. Stop the foreground server with Ctrl+C when finished.
For your own files, go directly to bring your own project; the guide’s earlier installation pin is historical.
Optional: try the older published literature dashboard
The PyPI package provides the older literature dashboard, not the newer source workspace. For an account-free sample, this separate virtual environment and empty root were tested on Linux with Python 3.12:
Use a new or empty research-hub-preview directory under HOME: the command creates .research_hub and logs there. It prints the generated temporary HTML path; open that path in your browser. The bare dashboard --sample failed in a fresh HOME without the root setting; see verification notes for platform and browser limits. For real services, see setup, the dashboard tour, and first 10 minutes.
Work in the workspace
[Historical workspace UI capture showing local demo project navigation and research records.]
Historical demo capture, reviewed 2026-09-08; the current interface may differ.
Your editor remains responsible for changes to original files; the workspace registers their paths and hashes. A resolvable identifier does not prove a source supports a claim: check the evidence and scientific judgments yourself.
Discover literature
In a compatible AI tool (an AI host) that can load the research-hub skill and has search and reading tools, start with a concrete request, for example:
Find literature on LLMs simulating human decisions; include original links, relevance, versions, and limits on available full text.
Then ask to focus on economic decisions and compare human baselines and evaluation methods. Review the sources, reading coverage, and open questions before deciding what to do next. Search snippets are not full-text reading. This research approach can be used independently of Hub; Zotero, Obsidian, NotebookLM, and Hub storage are optional. The Hub visual workspace and saved-result view do require Hub.
The native reader can organize supplied research summaries, source indexes, and bibliographies, and attach a PDF explicitly supplied by the user. The PDF is copied unchanged for download; that does not mean it was parsed, translated, verified, or read in full. The reader can display caller-supplied translations alongside original observations, labeled unverified; it does not generate translations or verify their accuracy. See the native reader export guide for the supplied-translation format.
See AI Research Skills, the AI host support matrix, and MCP/REST integration. The optional saved-result contract describes what a Hub handoff stores and its platform boundaries.
Write, review, and deliver
The optional writing setup explains how to verify and configure the adapter. Connected Codex receives bounded text excerpts, not binary document contents. Use your editor for Word formatting, LaTeX compilation, and final document changes. Accepted proposals can be packaged into a local ZIP after separate approval; this does not authorize publication or cloud upload. Workspace approval does not automatically protect existing direct-write CLI, MCP, dashboard, or cloud tools. See boundaries and recovery.
Optional integrations
- Zotero: manage references; the connection requires an API key and library ID.
- Obsidian: organize notes in a local vault, or begin with local files.
- NotebookLM: create source-based briefings; it requires browser sign-in and a working session. See setup and troubleshooting.
- AI hosts: connect through MCP/REST or portable skills; MCP requires the optional
[mcp]extra.
Choose integrations as needed and run ./.venv/bin/python -m research_hub doctor (macOS/Linux) or .\.venv\Scripts\python.exe -m research_hub doctor (Windows PowerShell) to inspect them individually. Setup or installation does not itself verify a service. The setup guide covers extras and credentials; see also local file import, EZproxy, and the live smoke checklist.
Integration credentials and extras
The local workspace demo needs none of these credentials. Existing personas use optional extras: Researcher and Humanities [playwright,secrets]; Analyst and Internal KM [import,secrets].
Documentation and contributing
Source: README.md at commit f52800b
Tools
0Version history
1- v1.0.0LatestSep 16, 2026
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- Tools listed15 pts
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