mcp-techtrend

A single MCP server that pullsacademic + code + medical-device-regulatorytrend data from seven sources and renders newspaper-style briefings — with per-domain tuning baked in.

trends_briefingis 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-sourceand 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 viapython configure.py, thentrends_briefingbecomes the "Monday morning newspaper" for their domain.

- Newspaper formatwith translation hint — the LLM auto-translates source text (paper abstracts, recall reasons, etc.) to your conversation language while preserving identifiers, URLs, and metric values verbatim.
- Per-category round-robinfor arXiv —cs.HC(~50 papers/wk) doesn't get drowned bycs.LG(~1500/wk) when both are tracked together.
- TTL cache + concurrent-request coalescing— repeat calls and parallel briefings don't hammer upstream APIs.
- No required tokens.All seven sources work anonymously; tokens just raise the per-source rate limit ceiling.
- Sandbox-safe Python launcher.Bypasses theclaude_desktop_config.jsonenvblock (which truncates whitespace-containing values on some macOS builds) by setting environment variables in Python before handing off to the server.

git clone https://github.com/salwks/mcp-techTrend.git cd mcp-techTrend python3 -m venv .venv .venv/bin/pip install -r requirements.txt

Connect to Claude Desktop by editing~/Library/Application Support/Claude/claude_desktop_config.json:

{ "mcpServers": { "trends": { "command": "/path/to/trends-mcp/.venv/bin/python", "args": ["/path/to/trends-mcp/run.py"] } } }

⚠️argspoints atrun.py(the launcher),nottrends_mcp.py. The launcher sets domain-specific env vars before the server starts.

Restart Claude Desktop. Thetrendsserver should appear with the tools listed below (count depends on your enabled sources).

One source of truth:run.py.Two ways to edit it:

A. Interactive TUI —configure.py(recommended)

═══ trends-mcp 설정 ═══ [1] Active sources (7/7 enabled) [2] arXiv categories (4 entries · 13 papers/wk) [3] PubMed query [4] API tokens (0/4 set) [5] Show current config [6] Save and restart [7] Quit without saving

Toggle sources with numbers, set arXiv weights withset 1 7, apply presets withpreset medical-imaging, save with[6]. The save action backs up torun.py.bak, writes the new SETTINGS block (AST-based — never touches non-config code), and runspkill -f trends_mcpso 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.

python configure.py --show # print current config python configure.py --restart # pkill stale MCP processes

TRENDS_ENABLED_SOURCES = "" # "" = all TRENDS_ARXIV_CATEGORIES = "cs.LG:5,cs.CV:3,cs.CL:3,cs.AI:2" TRENDS_DEFAULT_PUBMED_QUERY = "(deep learning OR AI) AND (medical OR clinical)" # GITHUB_TOKEN = "ghp_..." # raises 60 → 5,000 req/h # HF_TOKEN = "hf_..." # NCBI_API_KEY = "..." # raises 3 → 10 req/s for PubMed # OPENFDA_API_KEY = "..." # raises 240 → 120,000 req/day

Restart Claude Desktop after saving (orpkill -f trends_mcp).

Same SETTINGS block, edited via MCP tool calls. The chat path andconfigure.pyread & write the samerun.py(single source of truth), so changes from either side are visible to the other.

"트렌드에서 PubMed 쿼리를 cardiology 쪽으로 바꿔줘" "github와 arxiv만 켜둬" "GitHub 토큰 등록할게: ghp_..."

The host Claude picks the righttrends_set_tool and confirms what changed. After any change,restart Claude Desktop(or runpkill -f trends_mcpin a terminal) — the MCP server reads the SETTINGS block at spawn time.

# AI/ML researcher (default) TRENDS_ARXIV_CATEGORIES = "cs.LG:5,cs.CV:3,cs.CL:3,cs.AI:2" # Medical imaging / clinical AI TRENDS_ARXIV_CATEGORIES = "eess.IV:5,cs.CV:3,cs.HC:2,q-bio.QM:2" # Robotics TRENDS_ARXIV_CATEGORIES = "cs.RO:5,cs.AI:3,cs.LG:2,cs.CV:2" # HCI / UX TRENDS_ARXIV_CATEGORIES = "cs.HC:5,cs.CY:3,cs.AI:2,cs.SI:2" # Security TRENDS_ARXIV_CATEGORIES = "cs.CR:5,cs.LG:2,cs.NI:2" # Computational biology TRENDS_ARXIV_CATEGORIES = "q-bio.QM:4,q-bio.GN:3,q-bio.BM:3,stat.AP:2"

TRENDS_ENABLED_SOURCES = "arxiv,github,huggingface,paperswithcode" # → fda_510k, fda_recalls, pubmed tools won't appear in the tool list at all

All search tools acceptdays=Nfor recent-N-days filtering.trends_briefinggroups results into 🎓 Research / 💻 Code & Models / 🏥 Regulatory sections. The fivetrends__config/trends_set_tools are configuration mirrors ofconfigure.py— seeConfiguration § C.

Bioinformatics data for AI agents — gene search, protein structures, clinical variants, PubMed literature, and DNA sequences via NCBI and UniProt. No API key required.