The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the MCP TechTrend listing page.
한국어 문서: README.ko.md
A single MCP server that pulls academic + code + medical-device-regulatory trend data from seven sources and renders newspaper-style briefings — with per-domain tuning baked in.
| Source | Tools | Notes |
|---|---|---|
| arXiv | arxiv_recent, arxiv_search | Per-category round-robin so small categories aren't drowned by big ones |
| PubMed | pubmed_search | Full abstracts via efetch.fcgi |
| HF Daily Papers | paperswithcode_trending | Sorted by community upvotes (replaces sunset PwC API) |
| GitHub | github_trending, github_search | Trending page scrape + Search API with created:> date filter |
| Hugging Face | huggingface_trending | Models / datasets / spaces, trending or recent |
| openFDA 510(k) | fda_510k_recent | Device clearances |
| openFDA Recalls | fda_recalls_recent | Recall events with class filter |
| (aggregators) | trends_digest, trends_briefing | Multi-source parallel calls |
trends_briefing is the headline tool: invoke "weekly news" / "주간 뉴스" and
get a newspaper-formatted briefing across all enabled sources, automatically
translated into the user's conversation language by the LLM.
Most academic / code / regulatory MCP servers are single-source. This one is
multi-source and domain-aware: a researcher tracking medical-imaging AI,
an ML engineer following ML papers, a security analyst watching CVEs and
trending repos — all configure once via python configure.py, then
trends_briefing becomes the "Monday morning newspaper" for their domain.
What makes it useful:
cs.HC (~50 papers/wk) doesn't
get drowned by cs.LG (~1500/wk) when both are tracked together.claude_desktop_config.json
env block (which truncates whitespace-containing values on some macOS
builds) by setting environment variables in Python before handing off to
the server.Connect to Claude Desktop by editing
~/Library/Application Support/Claude/claude_desktop_config.json:
⚠️
argspoints atrun.py(the launcher), nottrends_mcp.py. The launcher sets domain-specific env vars before the server starts.
Restart Claude Desktop. The trends server should appear with the tools
listed below (count depends on your enabled sources).
One source of truth: run.py. Two ways to edit it:
configure.py (recommended)Toggle sources with numbers, set arXiv weights with set 1 7, apply presets
with preset medical-imaging, save with [6]. The save action backs up to
run.py.bak, writes the new SETTINGS block (AST-based — never touches
non-config code), and runs pkill -f trends_mcp so Claude Desktop respawns
the server with the new config on next call.
The TUI menu labels are in Korean; commands and presets are in English. i18n of the TUI itself is on the v0.2 roadmap.
Single-shot modes:
run.py SETTINGS blockRestart Claude Desktop after saving (or pkill -f trends_mcp).
trends_set_* toolsSame SETTINGS block, edited via MCP tool calls. The chat path and configure.py
read & write the same run.py (single source of truth), so changes from either
side are visible to the other.
Just say it in chat:
"트렌드에서 PubMed 쿼리를 cardiology 쪽으로 바꿔줘" "github와 arxiv만 켜둬" "GitHub 토큰 등록할게: ghp_..."
The host Claude picks the right trends_set_* tool and confirms what changed.
After any change, restart Claude Desktop (or run pkill -f trends_mcp in
a terminal) — the MCP server reads the SETTINGS block at spawn time.
| Tool | Purpose |
|---|---|
trends_get_config | Show current sources, categories, query, and which tokens are set (values never returned) |
trends_set_enabled_sources(sources) | Enable a subset; ["*"] or ["all"] for all |
trends_set_arxiv_categories(categories) | ["cs.LG:5", "cs.HC:3"]-style list |
trends_set_pubmed_query(query) | PubMed syntax (MeSH, [Title/Abstract] tags) |
trends_set_token(provider, value) | provider ∈ {github, hf, ncbi, openfda}; empty value clears |
Tokens: trends-mcp only does read operations, so create tokens with minimal scope — for GitHub, no scope at all (just authentication for rate limit). Don't put a
repo-scoped PAT here; it'd be over-permission.
Common arXiv categories (full reference: ARXIV_CATEGORIES.md):
| Code | Field | Weekly papers (approx) |
|---|---|---|
cs.AI | Artificial Intelligence | 500–800 |
cs.LG | Machine Learning | 1,500–2,000 (largest) |
cs.CV | Computer Vision | 1,000–1,500 |
cs.CL | NLP | 500–800 |
cs.HC | HCI / UX | 50–100 |
cs.RO | Robotics | 100–200 |
cs.CR | Security | ~200 |
eess.IV | Image/Video Processing (medical imaging) | 100–200 |
q-bio.QM | Quantitative biology | 50–100 |
Empty / "*" / "all" = enable everything. Disabled sources don't register
their tools, so the chat tool list itself shrinks. trends_digest and
trends_briefing remain registered and skip disabled sources gracefully.
| Tool | Purpose |
|---|---|
arxiv_recent | Recent papers in one category, by submission date |
arxiv_search | Keyword / field-syntax search (ti:, au:, abs:, cat:) |
pubmed_search | PubMed search (MeSH terms, field tags) — abstracts via efetch |
paperswithcode_trending | HF Daily Papers, sorted by community upvotes |
github_trending | Browse github.com/trending (HTML scrape) |
github_search | GitHub Search API; days filters by created: |
huggingface_trending | HF Hub models / datasets / spaces |
fda_510k_recent | Recent FDA 510(k) clearances |
fda_recalls_recent | Recent FDA medical-device recalls (class filter) |
trends_digest | Multi-source bullet-list digest, given a topic |
trends_briefing | Multi-source newspaper briefing; topic optional |
trends_get_config | Show current settings (token values never returned) |
trends_set_enabled_sources | Toggle which sources are active |
trends_set_arxiv_categories | Set arXiv categories + per-category weights |
trends_set_pubmed_query | Set the default PubMed query |
trends_set_token | Set / clear a rate-limit booster token |
All search tools accept days=N for recent-N-days filtering. trends_briefing
groups results into 🎓 Research / 💻 Code & Models / 🏥 Regulatory sections.
The five trends_*_config / trends_set_* tools are configuration mirrors
of configure.py — see Configuration § C.
trends_digest vs trends_briefingtrends_digest | trends_briefing | |
|---|---|---|
| Topic | required | optional ("what's new" mode) |
| Source range | configurable subset (default 4) | all enabled sources |
| Format | bullet-list digest | grouped newspaper format |
| Use case | topic deep-dive | regular weekly briefing |
Per-process in-memory TTL cache wraps every HTTP response. Concurrent
identical requests are coalesced via per-key asyncio.Lock — N parallel
callers fire one upstream request.
| TTL group | Length | Tools |
|---|---|---|
| Trending | 5 min | github_trending, paperswithcode_trending, huggingface_trending (trending sort), github_search (with days) |
| Default | 10 min | arxiv_recent, arxiv_search, github_search, huggingface_trending (other sorts) |
| Static | 1 hour | pubmed_search, fda_510k_recent, fda_recalls_recent |
Up to 256 entries; oldest evicted when full. No way to disable — TTLs are short enough that staleness is bounded.
github_search with
days=7 and sort=stars.trendingScore is undocumented. API surface may change.classification field sometimes returns None even on
recently classified recalls (upstream data lag). Search index lags too.