JW Research MCP
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@JW Research MCPsearch WOL for 'hope'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
JW Research MCP
A remote Model Context Protocol server for traceable research across JW.org and
the Watchtower Online Library. This project extends
advenimus/jw-mcp with full WOL
articles, publication pagination, direct library search, Study Bible footnotes,
full-text cross-references, daily texts, caching, and optional server-side
research synthesis with Kimi. Paragraphs, scriptures, related articles, and
publication images retain direct source links for verification.
What is preserved
The original tool names and workflows remain available:
search_bible_booksget_bible_verseget_verse_with_studyget_bible_verse_urlgetWorkbookLinks/getWorkbookContentgetWatchtowerLinks/getWatchtowerContentget_jw_captions
get_verse_with_study.fields now also accepts footnotes. WOL exposes
translation footnotes separately from both study notes and marginal
cross-references, so no content is duplicated between those fields.
Related MCP server: JW MCP Server
Research tools
Tool | Purpose |
| Full translation footnotes for a verse |
| Complete article with paragraph anchors, live inline links, images, and related material |
| Paginated full-size images, thumbnails, captions, alt text, and exact source anchors |
| Linked subheadings and WOL-recommended similar material |
| Bounded publication slices by sequential TOC entry and paragraph page |
| Direct article URLs, including natural TOC pages for large works |
| Direct WOL full-text search |
| Topic search for images across matching WOL articles |
| Marginal references with complete cited verse text |
| Daily scripture and comment for a date |
| Conversational Kimi K3 synthesis with evidence, URLs, confidence, gaps, and follow-ups |
All network-backed responses contain:
{
"metadata": {
"source_url": "https://...",
"timestamp": "2026-07-28T00:00:00.000Z",
"cache_hit": false
}
}The default cache TTL is 15 minutes. Retrieval tools accept langwritten;
supported WOL routes currently include E, S, F, X, I, T, J,
KO, and U. Research retrieval tools support format: "json" and
format: "markdown".
Markdown output uses clickable titles, paragraph source anchors, scripture references, footnotes, related articles, and image links. JSON output retains both plain text and source URLs for programmatic use.
Deep and conversational research
analyze_research supports four modes:
answer— direct evidence-based responseexplore— map themes and connectionscompare— contrast publications, passages, or time periodsverify— audit a claim and identify missing evidence
Use depth: "focused", "deep", or "exhaustive". For follow-up questions,
pass a concise conversation_context; it preserves continuity but is never
treated as source evidence. Every result includes a short answer, deep
synthesis, source-linked key points, confidence ratings, consistency or
tension findings, uncertainties, a source index, and suggested follow-ups.
For maximum accuracy, retrieve broad evidence in bounded pages first, include
each block's source and source_url, and then call analyze_research.
Publication pagination
get_book_content treats chapter as a 1-based sequential entry in the
publication TOC. A call returns at most three chapters and 25 paragraphs per
chapter. Use page and next_page, or an explicit paragraph_range, to walk
the content without placing an entire bound volume in one model context.
{
"publication_code": "it",
"chapter_range": "1-3",
"page": 1,
"page_size": 15,
"langwritten": "E",
"format": "json"
}For large reference works such as Insight on the Scriptures,
get_publication_toc also exposes WOL's natural TOC pages.
Local development
Requires Node.js 20 or newer.
npm install
npm run typecheck
npm test
npm startTo test Streamable HTTP:
cp .env.example .env
npm run build
MCP_TRANSPORT=http MCP_AUTH=false npm run start:httpThen run the MCP Inspector:
npx @modelcontextprotocol/inspectorConnect it to http://localhost:8080/mcp.
The live WOL smoke test is:
npm run build
node scripts/smoke-live.mjsEnvironment variables
Variable | Default | Description |
|
| Use |
|
| HTTP listen port |
| local URL | Public Railway URL used in OAuth metadata |
|
| Set |
| — | Required when OAuth is enabled; minimum 8 characters |
| — | Required only by |
|
| Kimi model used for research synthesis |
|
| OpenAI-compatible Kimi API base URL |
|
| In-memory fetch cache TTL |
|
| Default |
Railway
The included multi-stage Dockerfile compiles TypeScript and the included
railway.toml uses /health for deployment health checks. Configure the
environment variables above, deploy, generate a Railway domain, then set
MCP_BASE_URL to that exact https://... domain and redeploy.
The MCP endpoint is:
https://YOUR-RAILWAY-DOMAIN/mcpKeep this connector separate from existing services until its retrieval and analysis behavior has been verified with your own research workflow.
Tests
The automated suite verifies:
footnotes remain distinct from study notes and cross-references
full-article paragraph numbering and marker preservation
linked paragraph citations, media captions, and related-material parsing
hard paragraph pagination bounds
cache-hit behavior
localized WOL route construction
schema-validated
analyze_researchJSON without Markdown fences
The live smoke test additionally verifies a real Insight TOC and pagination, WOL search, article media, related research trails, full-text cross-references, daily text parsing, and cached repeats.
Attribution and license
Forked from advenimus/jw-mcp.
Licensed under the MIT license of the upstream project.
Maintenance
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