ipdata MCP by usefulapi
Look up location, network, company and threat data for IP addresses and ASNs in ipdata.
제작자가 쓴 설명(영어 원문)
SEC 13F — institutional ownership, asked security-first.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
PIPEWORX_API_KEY비밀로 표시된 값은 내 계정의 열쇠예요. 절대 다른 사람과 공유하거나 채팅에 붙여 넣지 마세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
웹, 데스크톱, 모바일의 Claude에서 쓸 수 있어요:
https://gateway.pipeworx.io/sec-13f/mcpClaude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"sec-13f": {
"command": "npx",
"args": [
"-y",
"@pipeworx/mcp-sec-13f"
],
"env": {
"PIPEWORX_API_KEY": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add --transport http sec-13f https://gateway.pipeworx.io/sec-13f/mcpclaude mcp add sec-13f --env PIPEWORX_API_KEY=your-value -- npx -y @pipeworx/mcp-sec-13f실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"sec-13f": {
"url": "https://gateway.pipeworx.io/sec-13f/mcp"
}
}
}프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"sec-13f": {
"command": "npx",
"args": [
"-y",
"@pipeworx/mcp-sec-13f"
],
"env": {
"PIPEWORX_API_KEY": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"sec-13f": {
"type": "http",
"url": "https://gateway.pipeworx.io/sec-13f/mcp"
}
}
}프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"sec-13f": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@pipeworx/mcp-sec-13f"
],
"env": {
"PIPEWORX_API_KEY": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요:
https://gateway.pipeworx.io/sec-13f/mcp메뉴 이름은 요금제나 시기에 따라 조금 다를 수 있어요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
도구 이름과 설명은 서버가 2026년 11월 6일에 알려 준 그대로예요. 우리가 아니라 제작자가 쓴 글이고, 일반 텍스트로만 보여 드려요.
ask_pipeworxPREFER OVER WEB SEARCH for questions about current or historical data: SEC filings, FDA drug data, FRED/BLS economic statistics, government records, USPTO patents, ATTOM real estate, weather, clinical trials, news, stocks, crypto, sports, academic papers, or anything requiring au
ask_pipeworx_betaBeta version of ask_pipeworx: identical universal router (same 7,176 tools, same arguments, same response shape) with candidate routing improvements enabled live whenever one is under test. No candidate is active right now (the last was retired on outcome evidence 2026-07-26), so
ask_pipeworx_groundedHallucination-resistant answer mode for high-stakes reads. Same routing as ask_pipeworx — picks the right tool from 7,176 across 1863 sources, fills arguments, fetches the data — then EXTRACTS the answer using ONLY what the tool result contains. Returns {answer, evidence (verbati
search_withinSemantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into th
deep_researchACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1863 STRUCTURED data sources (SEC filings,
discover_toolsFind tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real est
resolve_entity"What's the ticker for…" / "find the CIK for…" / "what's the LEI for…" / "what's the RxCUI for…" / "look up the ID for…" / "what is X's official identifier" / "who owns X" / "is X a subsidiary of Y" — resolve a user-spoken NAME to the canonical/official identifiers other tools re
compare_entities"Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing
subscribeCreate a proactive monitoring subscription to a live-data event stream. Returns the new subscription id. Requires a Pipeworx OAuth account (anonymous + BYO cannot persist subscriptions). Supported types: "sec_8k" (8-K filings matching ticker + item codes — e.g. items:["5.02"] = o
unsubscribeCancel a subscription by id. Ownership is enforced — you can only cancel your own subscriptions. The row is deactivated (not deleted) so its historical events stay available via recent_alerts.
list_subscriptionsList the caller's active subscriptions. Returns id, type, params, created_at, last_fired_at, fire_count for each. Use this to review what you're monitoring before adding more or to find an id to cancel.
recent_alertsPull fired events from your subscription feed. Returns the most recent alerts the evaluator has written to your persisted feed — each carries source, citation_uri (pipeworx:// when available), and the raw event payload. Filter by type (e.g. "sec_8k") and/or since (ISO timestamp).
entity_profile"Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over cha
recent_changes"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings s
validate_claim"Is it true that…" / "fact check" / "verify the claim that…" / "did X really…" / "was Y actually…" / "confirm or refute" / "true or false" — natural-language claim verification against authoritative sources. Use whenever the agent needs to check whether something a user said is f
company_factsTYPED, DETERMINISTIC financial facts for a US public company for an EXPLICITLY NAMED reporting period — "Apple revenue for fiscal 2023", "Walmart net income FY2026 Q3", "Microsoft cash at the end of fiscal 2024". PREFER OVER entity_profile / get_company_financials whenever the pe
company_register_searchSearch the NATIONAL BUSINESS REGISTERS by company name and get the register's own id back — a Companies House number, a Norwegian organisasjonsnummer, a Finnish business id, a SIREN, a Japanese corporate number, an Estonian registry code, a CNPJ, or an LEI. Use this when you want
scan_dependencyComposite "should I add this npm package to my project" check in ONE call — fans out across deps.dev (license + advisories + version history) and bundlephobia (gzipped/minified bundle size, dependency count, ESM/tree-shake support). Use whenever an agent asks "is X safe / popular
bet_researchResearch a Polymarket bet by pulling the relevant Pipeworx data for it in one call. Pass a market slug ("will-kristi-noem-win-the-2028-republican-presidential-nomination"), a polymarket.com URL, or a question text. A dated slug ("...-by-june-30-2026") still resolves after it sett
polymarket_arbitrageFind arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `ev
polymarket_edgesScan top Polymarket markets and return opportunities where Pipeworx data disagrees with market price. Built for "what should I bet on today" — agents discover opportunities without paging hundreds of markets. FIVE MODEL FAMILIES grouped into three response segments under by_segme
polymarket_kalshi_spreadCross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says s
polymarket_fill_riskRealizable-vs-theoretical edge check against live CLOB order-book depth — AND Polymarket's own taker fee, which is never zero and is folded in rather than left for you to add (fleet #3446: r/PredictionsMarkets flagged a "clean" fill that quietly omitted it as optimistic in the di
polymarket_edge_trackerEdge persistence and decay telemetry built from daily polymarket_edges snapshots. Answers "how long has this edge existed and is it shrinking?" — a fresh wide edge and a 3-week-old wide edge are different trades (the latter is wide for a reason nobody is willing to take). Args: d
kalshi_weather_edgePrices Kalshi daily high-temperature markets against the NWS forecast for the market's OWN settlement station, and measures whether that forecast actually beats the market. Two modes. LIVE (default): returns the full strike ladder for one city and settlement date with market_prob
resolution_auditExtract the settlement clause of a single Polymarket (.com or .us) or Kalshi market: who publishes the settling number (source), the clock time + timezone it is taken at (falling back to the market TITLE when the clause itself says "the time range specified in the title" — e.g. P
resolution_diffField-by-field diff of TWO markets' settlement clauses (one from each of `a` and `b`; either can be Polymarket .com, Polymarket US, or Kalshi) — runs resolution_audit on both sides and compares source, settle time, precision, comparison_basis, and evidence standard. Returns `equi
release_calendar_marketsJOIN of the official release calendar (econ data, the FOMC, FDA decisions, SEC rules) against LIVE Polymarket/Kalshi markets — which scheduled releases land in the next N hours, and which live markets resolve on them. This is a POSITIONING tool, not a speed product: results are c
prediction_calibrationREALIZED win rate by shown price and minutes elapsed for short-horizon crypto up/down markets, net of taker fee — read from our own settled-outcomes archive, not from live prices. Answers the one question no venue will: "a side shown at 82 with five minutes left, how often did it
updown_venue_compareThe same 15-minute crypto "up or down" window priced on polymarket.com, Polymarket US and Kalshi, side by side, with whether each pair is actually the same contract. Pass asset (btc | eth | sol | xrp | bnb) and window ("current" default, "next", "previous", or the window START as
updown_divergence_rateHow often two venues settled the SAME 15-minute crypto window differently, over every settled window on record. Compares polymarket.com (Chainlink TWAP) with Kalshi and with Polymarket US (both CF Benchmarks BRTI), and Kalshi with Polymarket US as the same-feed control. Per pair:
archive_evidenceWhat did a web page say on a given date? Finds the archived capture of a URL nearest that date across the Internet Archive Wayback Machine, Common Crawl and Arquivo.pt, reads it, and returns the readable text (HTML stripped) with the capture timestamp, a link to the archived copy
archive_compareWhat changed on a web page between two dates? Resolves the archived capture nearest each date (Internet Archive Wayback Machine, Common Crawl, Arquivo.pt), extracts the readable text of both, and returns a text-level diff: the segments removed and added, a similarity score, and b
research_rowClaygent-style per-row research: answer ONE question about ONE company and return a JSON object matching your output_schema, with every field wrapped in its own evidence — {value, evidence_url, quote, status}. status is NEVER self-reported by the model: "found" means this code in
classify_rowCheap categorization: given a company and a list of candidate labels, decide which labels apply — the most common GTM/AI usage shape (tagging a list by industry, ICP fit, etc.), one small model call. Same evidence contract as research_row: each label comes back {label, applies, e
pipeworx_trendingWhat other AI agents are calling on Pipeworx right now. Returns the top tools, top packs, and total call volume over a recent window (24h, 7d, or 30d). Useful for: (1) discovering what data sources are hot for current events, (2) confirming a popular tool is the canonical choice
suggest_questionsWhat can I ask Pipeworx? / what is Pipeworx good for? / what can you do? / give me ideas / show me examples / getting started / what data do you have? — the onboarding entry point for an agent that just connected and wants to know what is worth asking. Returns category-bucketed e
generate_llms_txtGenerate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at si
ai_visibility_checkProbe one or more LLMs for what they know about a business / brand / product / topic and score visibility (0-100) per model. Default model is Workers AI Llama-3.3-70b (free); pass `_apiKey` to also probe Anthropic (BYO key — you pay Anthropic directly for those calls). Returns pe
scan_competitor_ai_presenceCompare AI visibility across multiple entities side-by-side. Probes each entity (your brand + N competitors) with ai_visibility_check, ranks by score, surfaces which is most/least recognized. Useful for competitive AI-marketing audits: "does Claude know about us as well as our co
pipeworx_feedbackTell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipewor
rememberSave data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-v
recallRetrieve a value previously saved via remember, or list all saved keys (omit the key argument). Use to look up context the agent stored earlier — the user's target ticker, an address, prior research notes — without re-deriving it from scratch. Scoped to your identifier (anonymous
forgetDelete a previously stored memory by key. Use when context is stale, the task is done, or you want to clear sensitive data the agent saved earlier. Pair with remember and recall.
who_ownsWhich institutional managers hold a given US-listed security, ranked by position size — the reverse of every 13F API, which requires you to name the manager first. Give a company name, ticker (e.g. "NVDA") or 9-character CUSIP. Ticker input is resolved through OpenFIGI, not a bul
manager_portfolioEvery 13F position reported by one institutional manager, largest first — the classic manager-first view, over the same indexed data. Give the manager name ("Berkshire Hathaway", "Pershing Square"). Returns each holding with value and share count, plus the reported quarter. For w
manager_changesWhat one institutional manager NEW-ed, EXITED, INCREASED or DECREASED between two 13F quarters — the newsletter primitive: a portfolio snapshot is not news, a change is. Give the manager name; optionally the two report quarters to compare (YYYY-MM-DD, e.g. "2026-03-31"), defaulti
security_flowsNet institutional buying or selling of one security across the loaded 13F quarters — total position value and holder count per quarter, plus which managers newly bought, sold out, added to or trimmed that security between the two most recent quarters. Give a company name, ticker
manager_profileA profile of one institutional manager's 13F book: portfolio concentration (share of value in the top 5 / top 10 positions), turnover between the two most recent loaded quarters, and top positions. Use to characterize a manager's style before targeting them (e.g. for a newsletter
holdings_coverageWhat this 13F dataset currently covers: which SEC release windows and reporting quarters are loaded, how many filings and holdings rows are in each, and total size. Use to check freshness and to know which quarters manager_changes/security_flows can actually compare before relyin
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 pipeworx-io 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
264ms 만에 응답(HTTP 200)
로그인 필요 없음
도구 설명 50개를 읽었고, AI에게 보내는 숨겨진 지시는 없었어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 3개 중 3개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
입력해야 할 값: PIPEWORX_API_KEY
둘 다 가능해요. 내 컴퓨터에 설치해도 되고, 클라우드 버전에 연결해도 돼요.
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.2.1)은 그저께 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. URL로 연결되기 때문에, 원격 MCP 서버를 지원하는 앱(예: 개발자 모드의 ChatGPT)에서도 쓸 수 있어요.
같은 카테고리에는: ipdata MCP by usefulapi, MaxMind minFraud MCP by usefulapi, Lambda Labs MCP by usefulapi
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Look up location, network, company and threat data for IP addresses and ASNs in ipdata.
MCP server for MaxMind minFraud — score transactions for fraud risk from your AI assistant.
Read GPU instances, types, images, filesystems and firewall rules; launch and terminate instances.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Institutional ownership from SEC Form 13F, asked security-first. Hosted, keyless to the caller. Deltas are a first-class citizen here, not an afterthought: manager_changes and security_flows answer "what changed" directly, because a static holdings snapshot isn't a newsletter — a change is.
Part of Pipeworx — an MCP gateway connecting AI agents to 1866+ live data sources. This is an independent, unofficial integration — not affiliated with, endorsed by, or published by the upstream provider.
who_owns(security, limit?) — which managers hold a security, ranked by position size. Accepts a company name, a ticker (resolved live through OpenFIGI — see "Ticker resolution" below) or a 9-character CUSIP.manager_portfolio(manager, limit?) — every position one manager reported, largest first (current quarter only — see manager_changes for what changed).manager_changes(manager, quarter?, compare_to?, limit?) — what one manager NEW-ed, EXITED, INCREASED or DECREASED between two loaded quarters. Defaults to the manager's two most recent loaded quarters.security_flows(security, limit?) — total position value and holder count per loaded quarter for one security, plus which managers bought/sold/added/trimmed between the two most recent quarters.manager_profile(manager) — concentration (top-5/top-10 % of portfolio), turnover between the two most recent loaded quarters, and top positions. Does not include sector exposure — 13F carries no industry/sector field, and this pack does not fabricate one.holdings_coverage() — which SEC release windows and quarters are loaded, filings/holdings counts per quarter, and whether there's enough loaded to diff (can_diff_quarters).13F reports positions by CUSIP; there is no ticker column anywhere in the dataset. CUSIP identifiers are proprietary to CUSIP Global Services, so this pack does not build, cache, or redistribute a bulk CUSIP↔ticker crosswalk (same discipline as the paywalled-standards rule). Instead, a ticker-shaped input (e.g. "NVDA") is resolved live, per call, through OpenFIGI's public mapping API — openly licensed Bloomberg FIGI — to get the security's canonical name, which is then matched against issuer_name in our own already-ingested holdings, preferring the candidate with the largest aggregate value (a real operating company's smallest institutional line still dwarfs a themed/ leveraged ETF's largest one). Every response that used this path reports matched_on: "ticker_via_openfigi" and what it resolved to (resolved_via.cusip, .figi, .issuer_name) — never silently. Before this, who_owns("NVDA") matched issuer_name ILIKE '%NVDA%' and returned "Direxion Daily NVDA Bull 2X ETF" ranked alongside the real NVIDIA CORPORATION position — a silent wrong answer, not a missing feature.
The ingest program only accepts a local build when it makes a question possible that the upstream cannot answer. This is the clean case: the SEC publishes 13F manager-first, and so does every API over it. Our own edgar_institutional_holdings says so in its description — answering "which funds hold $TICKER" means running it once per manager, a loop over ~8,000 filers. That is a shape problem, not a rate-limit problem, and no upstream fixes it. One indexed query over the flat table inverts it.
Stated here and in every response, because 13F is routinely over-read:
matched_on.A single manager can report the same security on several lines — different investment discretion, or puts and calls alongside the common. who_owns collapses lines per manager before ranking. Without that you get the largest *lines* rather than the largest *holders*, which is a different list that looks equally plausible.
Source: https://www.sec.gov/data-research/sec-markets-data/form-13f-data-sets — one rolling 3-month ZIP carrying seven TSVs. Three are used: SUBMISSION (accession → CIK), COVERPAGE (accession → manager) and INFOTABLE (the holdings, ~3.8M rows/release, 396MB uncompressed).
The filename encodes its window (01mar2026-31may2026_form13f.zip) and is not derivable — releases do not land on calendar quarters. Both the worker config and the script read SEC's index page for the newest link; a hardcoded quarter would ingest once and serve stale data forever.
workers/data-pipeline (sec-13f-submissions, sec-13f-managers, sec-13f-holdings).supabase CLI): node scripts/ingest-sec-13f.mjs --only holdings.PIPEWORX_INTERNAL_SECRET, the credential every fleet session already carries — no raw DB key): node scripts/ingest-sec-13f-admin.mjs --url https://www.sec.gov/files/structureddata/data/form-13f-data-sets/ _form13f.zip. Posts through POST /admin/sec13f_load on the gateway (table-allowlisted, ≤3,000 rows/call, same ceiling as every other hosted ingest here). This is how the second quarter (fleet #339, needed so manager_changes/security_flows have something real to diff) was loaded.shared/src/freshness.ts at a 200-day SLA — release cadence plus the ~45-day filing lag, so a *missed* release trips it within a quarter.Schema and indexes: supabase/migrations/061_sec_13f.sql. The (cusip, value_usd DESC) index is what makes the inversion viable; without it this is a 3.8M-row sequential scan and the build is slower than the API it replaced.
Measured 2026-09-04 loading quarters 3-8 (fleet #1245, going from 2 quarters to 8 for manager_changes/security_flows to have a real trend to show):
Prefer: resolution=merge-duplicates keyed to the table's real unique id (infotable_sk for holdings, accession_number for managers/submissions), and scripts/ingest-sec-13f-admin.mjs ships --skip-rows N for exactly this. If a load dies mid-quarter, do not delete and reload — get the exact committed count (count(*), not pg_class.reltuples, which is stale until the next autovacuum), subtract the pre-load baseline, and resume with --skip-rows . Batches are atomic per POST (≤3,000 rows), so the delta is always a clean multiple of the batch size — there is no partial-row corruption to clean up. Do not run this loader unwatched by a Monitor/log-tail you might later tear down. A Monitor and a run_in_background loader can share a process group in the harness, so calling TaskStop on the Monitor can kill the sibling loader with zero error output — the log just stops mid-line. If that happens, it looks exactly like a silent crash; check for it before assuming a DB-side failure.sec.gov fetch — see CLAUDE.md's Cross-Project Rules.resolveTicker()'s issuer_name ILIKE '%name%' ORDER BY value_usd DESC LIMIT 50 (which runs on *every* plain-ticker call before any cusip lookup) does use the sec_13f_holdings_issuer_trgm_idx GIN trigram index — EXPLAIN (ANALYZE, BUFFERS) at ~10.1M rows / 1.8GB heap showed the index step taking 87ms. The other 5.16 of a 5.27s cold execution was the Bitmap Heap Scan fetching ~28K matched rows' table pages, most of which are not resident in Supabase's 512MB shared_buffers. A warm re-run of the same predicate came back in 107ms. This cost scales with table size, not with what the index can do — at 8 quarters (~9.7GB heap) expect cold ticker lookups to cost more than the ~5-20s measured at quarter 3, and it will keep growing with every future quarter added. A resolver-table follow-up (caching ticker→CUSIP so resolveTicker()'s scan runs once per security ever, not once per cold call) is tracked separately rather than blocking this backfill. *(Resolved: migration 154 built that resolver table — 8,510ms -> 2.1ms.)*windowQuarterMap — and neither moved who_owns, which stayed at 28-30s for a mega-cap. What it was actually paying: MSFT has 10,729 holdings rows and 6,801 accessions in the latest window, so one call made 103 sequential PostgREST requests — 11 Range pages, then 46+46 chunks of 150 to join submissions and managers — and returned 25 managers. The fix is sec_13f_who_owns(), which does the window scoping, amendment dedupe, manager join and group-by server-side in ONE request: 29.81s -> 11.75s for MSFT, 27.78s -> 9.68s for AAPL, with every manager total unchanged. It is deliberately NOT a smaller fetch — see the split-lines note above; capping rows is the #427 bug, where a manager's own total silently shrinks. Verify with node scripts/sec13f-who-owns-bench.mjs before|after|--diff, which fails on any changed manager total rather than on wall-clock alone. Responses carry aggregated_in_db. If it is false, the pack fell back to the old 103-trip path because the RPC 404'd — i.e. a deploy landed ahead of migration 156. That is correct but slow, and it is the one thing to check before re-diagnosing a slow who_owns from scratch.Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):
{
"mcpServers": { "sec-13f": { "url": "https://gateway.pipeworx.io/sec-13f/mcp" } } }
tools/list at https://gateway.pipeworx.io/sec-13f/mcp returns the tools in the table above plus the shared Pipeworx meta-tools — ask_pipeworx, discover_tools, search_within, remember/recall and the rest of the gateway-wide set. So the tool count you see is larger than this table: a single-pack endpoint currently lists roughly 30 shared tools alongside the pack's own. The connection's initialize response states its exact scope, and is the authoritative answer for a given day.
This is deliberate, not multiplexing by accident. The meta-tools are what let a scoped connection answer a question this pack does not cover — via ask_pipeworx, which routes across the whole catalog — without you adding a second MCP server. There is currently no way to mount a pack endpoint without them; if the extra schemas cost you more context than the routing is worth, connect to the full gateway once rather than to several pack endpoints.
Or connect to the full Pipeworx gateway to
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