原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Sec 13f

作者:pipeworx-io版本 0.2.1i★ –i电脑或云端
注册名称io.github.pipeworx-io/sec-13f

安装

概览

作者提供的说明(英文原文)

SEC 13F — institutional ownership, asked security-first.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 电脑或云端
  • 传输方式: stdio, Streamable HTTP
  • 分类: 网络安全
  • 你需要填写:PIPEWORX_API_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • 在云端运行无需安装任何东西,通过互联网连接
  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

适用于网页版、桌面版和手机版 Claude:

  1. 打开 Settings → Connectors
  2. 点击 Add custom connector
  3. 粘贴下面的地址,然后点击 Add
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Add2https://…3
https://gateway.pipeworx.io/sec-13f/mcp

或者在你的电脑上运行

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "sec-13f": {
      "command": "npx",
      "args": [
        "-y",
        "@pipeworx/mcp-sec-13f"
      ],
      "env": {
        "PIPEWORX_API_KEY": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add --transport http sec-13f https://gateway.pipeworx.io/sec-13f/mcp

或者在你的电脑上运行

claude mcp add sec-13f --env PIPEWORX_API_KEY=your-value -- npx -y @pipeworx/mcp-sec-13f

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "sec-13f": {
      "url": "https://gateway.pipeworx.io/sec-13f/mcp"
    }
  }
}

或者在你的电脑上运行

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "sec-13f": {
      "command": "npx",
      "args": [
        "-y",
        "@pipeworx/mcp-sec-13f"
      ],
      "env": {
        "PIPEWORX_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "sec-13f": {
      "type": "http",
      "url": "https://gateway.pipeworx.io/sec-13f/mcp"
    }
  }
}

或者在你的电脑上运行

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "sec-13f": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@pipeworx/mcp-sec-13f"
      ],
      "env": {
        "PIPEWORX_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

ChatGPT 只能连接互联网上的服务器:

  1. 打开网页版 ChatGPT → Settings → Connectors (Apps)
  2. 点击 Create 或 Add(部分套餐需要先在 Advanced 中开启 Developer mode)
  3. 粘贴下面的地址,起个名字,然后保存
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Create2https://…3
https://gateway.pipeworx.io/sec-13f/mcp

菜单名称可能因套餐和版本不同而略有差异。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • PIPEWORX_API_KEY 机密 env
    Optional Pipeworx API key. Without it calls are anonymous and capped daily; a free key raises the cap.

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

工具名称和描述与服务器在 2026年11月6日 报告的完全一致。这些内容由作者撰写,不是我们写的;我们以纯文本形式显示。

  • ask_pipeworx

    PREFER 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_beta

    Beta 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_grounded

    Hallucination-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_within

    Semantic 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_research

    ACCOUNT 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_tools

    Find 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

  • subscribe

    Create 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

  • unsubscribe

    Cancel 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_subscriptions

    List 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_alerts

    Pull 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_facts

    TYPED, 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_search

    Search 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_dependency

    Composite "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_research

    Research 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_arbitrage

    Find 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_edges

    Scan 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_spread

    Cross-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_risk

    Realizable-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_tracker

    Edge 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_edge

    Prices 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_audit

    Extract 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_diff

    Field-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_markets

    JOIN 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_calibration

    REALIZED 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_compare

    The 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_rate

    How 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_evidence

    What 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_compare

    What 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_row

    Claygent-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_row

    Cheap 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_trending

    What 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_questions

    What 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_txt

    Generate 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_check

    Probe 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_presence

    Compare 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_feedback

    Tell 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

  • remember

    Save 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

  • recall

    Retrieve 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

  • forget

    Delete 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_owns

    Which 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_portfolio

    Every 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_changes

    What 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_flows

    Net 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_profile

    A 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_coverage

    What 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

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 pipeworx-io 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • ✓ 通过

    端点有响应

    在 264 毫秒内响应(HTTP 200)

  • – 不适用

    使用 OAuth 登录

    无需登录

  • ✓ 通过

    工具描述中没有隐藏指令

    已读取 50 个工具描述,未发现针对 AI 的隐藏指令

与“网络安全”中的其他服务器比较i

  • 星标数多于此分类中其他 1000 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 1000 个服务器的 93% 更新
  • 基础检查结果等于或优于此分类中其他 1000 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Sec 13f 安全吗?

它在 3 项适用的基础检查中通过了 3 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:PIPEWORX_API_KEY

它在我的电脑上运行还是在云端?

两种方式都可以:安装在你的电脑上,或者连接云端版本。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.2.1)于3天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。

有什么可以替代它?

同一分类中有:EchelonGraph CVE & Exposure, KillerSkills, Phishnoo Sandbox

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

EchelonGraph CVE & Exposure

CVE, KEV, EPSS, SBOM and advisory lookups; per-CVE exposure from Shodan data (© Shodan). Keyless.

作者:echelongraph起步阶段↓ 1360/周今天更新

电脑或云端✓ echelongraph.io

KillerSkills

Security verdicts for agent skills and MCP servers, from sandbox runs, before you install them.

作者:cyligence-karim正在增长↓ 3070/周今天更新

在你的电脑上运行

Phishnoo Sandbox

Explore synthetic security awareness metrics and file example threat reports.

作者:api.phishnoo.nl起步阶段今天更新

在云端运行✓ api.phishnoo.nl

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

@pipeworx/sec-13f

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.

Tools

  • 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).

Ticker resolution — deliberately NOT a CUSIP↔ticker table

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.

Why this is hosted rather than proxied

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.

What 13F does not tell you

Stated here and in every response, because 13F is routinely over-read:

  • Long US-listed equity only. Shorts, cash, bonds and non-US holdings are excluded by rule. "How much does X own" is answerable only inside that universe.
  • Quarterly, and late. Filed up to 45 days after the period end. It is a lagged snapshot, never a current position.
  • $100M floor. A manager under that threshold does not file at all, so absence is not evidence.
  • No ticker column. CUSIP is the only identifier of record; issuer names are as the filer typed them ("NVIDIA CORP"). A ticker search falls back to an issuer-name match and says so in matched_on.

One thing the numbers depend 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.

Data + refresh

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.

  • Standing path: workers/data-pipeline (sec-13f-submissions, sec-13f-managers, sec-13f-holdings).
  • Backfill / recovery (needs a Supabase service key or linked supabase CLI): node scripts/ingest-sec-13f.mjs --only holdings.
  • Backfill via the gateway's admin route (needs only 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.
  • Freshness: registered in 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.

Multi-quarter backfill — throughput, resume, and what degrades at depth

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):

  • ~870 rows/sec through the admin route, so one quarter's ~2.8-3.8M holdings rows takes ~1-2 hours, not minutes. Size 8 quarters of wall-clock time accordingly.
  • The loader is resumable, not all-or-nothing. Every write uses 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` shares one egress IP across the whole fleet and rate-limits by IP. Running this loader's ZIP fetch at the same time as any other lane's SEC bulk pull (Form 4/insider, EDGAR full-text, XBRL) tripped a 429 from SEC's Akamai front end with an extendable 10-minute timeout. Coordinate before starting a bulk sec.gov fetch — see CLAUDE.md's Cross-Project Rules.
  • Depth degrades `who_owns` on the ILIKE/ticker path — the index isn't the problem, the heap is. 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.)*
  • `who_owns` sums in the DB, and the reason is round-trip COUNT, not any one plan (fleet #1254, migration 156). Two plan fixes landed first — 154 above, and 155 for 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.

Quick Start

Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):

{

"mcpServers": { "sec-13f": { "url": "https://gateway.pipeworx.io/sec-13f/mcp" } } }

What this endpoint actually serves

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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