
xbrlkit
ai.robosystems由 robosystems.ai 发布v0.21.4更新于 Nov 2, 2026
Read SEC EDGAR and XBRL filings with an AI: 18 tools over the filing itself. Local, free, no account
发布方自己的服务:RoboSystems
概览
本地 MCP 服务器,把 SEC EDGAR 与 XBRL 申报文件读入内存,提供 18 个工具来查看报表、附注、正文与附件。
- 可以做什么
- 按股票代码、EDGAR 编号、LEI、本地 XBRL 包、iXBRL 文件或 holon/TAVI 文档加载申报文件
- 以表格形式取出财务报表与披露网络,查找短语对应的概念,按概念与期间或按维度取数
- 核对小计是否勾稽,完整阅读一条披露,并对主要文档正文做正则检索
- 阅读附件及无 XBRL 的表单(如 Form 4、13F),并全文检索 EDGAR 找出值得读的申报
- 把申报导出为 holon、TAVI、xBRL-JSON、ClawDog 或属性图,在浏览器中渲染;安装 lpg 扩展后还可对多个申报运行只读 Cypher
- 适用场景
- 适合以对话方式查阅某份 SEC 或 ESEF 申报:取资产负债表、核对小计、找出申报方自有的扩展概念,或在 10-K 正文中检索,而无需写脚本或搭建数据库。
- 运行要求
- 以 Python 包形式在本地运行,可用 uvx 或 pip 安装;服务器需 mcp 扩展,图工具需 lpg 扩展。从 EDGAR 或 filings.xbrl.org 获取文件需要网络,本地文件可离线使用。SEC_GOV_USER_AGENT(姓名与邮箱)为可选项,仅用于 EDGAR 请求。
安装
在 SourceWeft 中
- 打开 控制台中的 xbrlkit,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
xbrlkit
Work with XBRL filings above Arelle: fetch a filing, parse it once into a neutral typed model, and project that model into whichever portable representation you need — or hand it one of those representations and get the model back.
Three ways in — the SEC, everyone else through
filings.xbrl.org, and the filing itself: an
XBRL package or archive (.zip), an iXBRL document (.htm), a bare instance
(.xml), a filing directory, or an http(s) URL to any of them. Nothing about
the middle of this requires EDGAR, or a regulator at all — a report that was
never filed with anybody parses like one that was.
Five projections out, and three of those read back, so a report that was never an
SEC filing gets the same treatment. Another surface, the filing's text, reads
the primary HTML directly and needs neither Arelle nor the network. And
xbrlkit view puts a filing on screen.
It is also a local MCP server. The package stands alone — a library and a
CLI — but xbrlkit serve holds filings in memory and exposes them to Claude,
ChatGPT or any MCP client through eighteen shaped tools, which makes reading a
filing a conversation instead of a script: ask for a statement, the concepts
behind a phrase, what foots to a subtotal, a segment breakdown, an exhibit, or
a regex across the prose. Nothing is indexed and no database sits behind it —
every answer is read from the filing in memory, on your machine. With the lpg
extra it also writes several filings as one property graph — a company's years,
or its peers — and answers read-only Cypher over it.
What you can ask it →
Arelle stays the parser — nobody should reimplement DTS resolution. What it
does not give you is anything ergonomic to hold: ModelXbrl is a large
mutable object graph tied to a controller you have to close. XbrlModel is the
answer to that — stateless, single-filing, lossless, and the waist every
projection hangs off.
The one architectural rule: everything goes through XbrlModel. A feature
that reaches into Arelle's ModelXbrl directly is bypassing the waist, and
that is the change that turns a kit into a junk drawer.
What's in the box
model.py is the waist itself, schema/ declares the property graph's tables,
query.py runs SPARQL over a built holon, cypher.py runs read-only Cypher over
a built .lbdb or icebug-disk tree, and view.py is the loopback server
behind xbrlkit view and the view_filing tool.
Install
Exposes the xbrlkit CLI (build, fetch, query, view, cache, serve) and the
library. Three optional extras: xbrlkit[lpg] for the property graph as a
LadybugDB database and for querying it (pyarrow, LadybugDB), xbrlkit[icebug]
for the same graph as an experimental icebug-disk tree (pyarrow only) and xbrlkit[mcp] for
the MCP server. Install xbrlkit[mcp,lpg] for the server's graph tools.
From a source checkout:
SEC User-Agent
SEC fair access asks for a User-Agent identifying you with contact info.
EDGAR works out of the box under a default that names the project, and the
first unattributed fetch says so once — SEC rate limits per IP, so the shared
default costs nobody else their budget. Identifying yourself is a courtesy,
and one worth extending. just install already created your .env:
.env is loaded automatically by every command run from a checkout of this
repo — the lookup is relative to the installed code, not your working
directory, so a uvx or pip install never picks one up. There, use
export SEC_GOV_USER_AGENT=…, --user-agent (before the command), or an MCP
env block (see
Serve to an MCP client). Nothing outside EDGAR
needs it — a local file, a JSON report and filings.xbrl.org all load without.
Usage
From a source checkout, just wraps the same CLI: just build 320193 0000320193-23-000106 and just fetch NVDA.
As a library, a FilingSession resolves a filing the way view and serve
do, with no extra installed:
A host running its own Arelle goes a level down: xbrlkit.parse.load_model
returns the ModelXbrl, and to_xbrl_model(mx, filing) walks it into the
same model, given the filing's FilingMeta (CIK and accession).
Serve to an MCP client
Two ways to run it. They differ in which process does the fetching, and so in where your SEC identity goes.
stdio — the client launches the server. The identity belongs in the
server's own env block:
HTTP — you start the server, the client only points at a URL. An env
block in the client config would reach nothing here; set it on the command:
or, equivalently:
A .env file is not a channel for either of these. The lookup is relative
to the installed code rather than your working directory, so it resolves only
inside a checkout of this repo — a uvx or pip install never sees one. Use
the environment, the env block, or --user-agent before the command.
Both are optional: EDGAR works unattributed under the default, saying so once. And filings.xbrl.org, local packages and TAVI/holon JSON need no identity at all.
What you can ask it
Load a filing from the chat — a ticker, an EDGAR cik:accession, a lei: for
ESEF and the national regimes, a local package, or a holon or TAVI by path or
URL. A ticker or cik:accession loads the filing's published holon (or its
TAVI model) first when the RoboSystems CDN has one, falling back to EDGAR. That
copy is RoboSystems' parse of the filing, not the filing as filed, and the
answer's read_from says which one you have; --pure or
XBRLKIT_ARTIFACTS_URL="" parses it from EDGAR instead. Exports go to
~/xbrlkit/output unless --out-dir says otherwise. Then:
- Pull a statement as a table. The income statement, balance sheet, cash flow or equity statement — or any disclosure network — as rows in the filer's own order and labels, values per period column.
- Find the concept behind a phrase. "Revenue", "operating lease liability" → the qnames this filer actually reports, its own extension concepts included, ranked with fact counts and where each appears. You never have to guess a US-GAAP name.
- Get values by concept and period. Consolidated totals by default — no dimensional qualifier, the most precise of duplicate tags — or broken out by any axis the filing carries: segment, product, debt instrument, acquisition.
- Check whether a subtotal foots. The calculation children with their weights, the reported total against the sum computed from them, per period, with the difference.
- Read one disclosure whole. A note's rows with values, the same rows by
its own axes, its calculation arcs footed, and its tagged text beside the
numbers. The
disclosuresindex finds the right block first, cheaply. - Search the prose. Regex over the whole primary document — Items, the notes, the cover, the signatures, tagged or not. A pattern that matches more than fits in the answer says which sections the rest fall in, busiest first.
- Read the other documents. Exhibits, an 8-K's EX-99.1 earnings release — where the non-GAAP measures and guidance live, since no XBRL holds them — or a 13F's holdings table.
- Read the forms with no XBRL at all. A Form 4's transactions and holdings, a 13F's positions, as rows with the document's header fields beside them.
- Find filings worth reading. EDGAR full-text search across the corpus by phrase, form, date and filer, where every hit carries the id that loads it.
- Export or render it. Write the filing as holon, TAVI, xBRL-JSON, ClawDog, a LadybugDB graph or icebug-disk tree, or the parse itself; or open it as a rendered report in the browser and hand back the link.
- Stack filings and query across them (with the
lpgextra). Export several loaded filings as one graph — a company's years, or peers — and run read-only Cypher over it withrun_cypher: revenue by report and period, or a figure that one year's comparative restates.
No graph and no database sits behind any of it: every answer about a filing is
read from that filing, and the only graph run_cypher reads is one you asked
export_filing to write. Beyond fetching a filing and its documents, the one
outward call is search_filings, which asks EDGAR's own full-text index which
filings to go and read. Full detail,
including the tool table and the --pure profile, in
serve/.
Where it runs
RoboSystems. The
RoboSystems platform's SEC
pipeline is built on this package: filings are parsed with xbrlkit.parse
(load_model on the platform's own cache directory, then to_xbrl_model),
projected with to_holon, to_tavi_report and the
property-graph tables, the shared sec graph is declared from
xbrlkit.schema, and the full-text index behind its document search is built
from xbrlkit.text.
Filing Ladder. The Filing Ladder benchmark — one filing handed to the same language model in every representation — built its 26-filing corpus of 2024–2025 10-Ks and 10-Qs with this package. Each projection is a rung of the ladder, so its published results are also a measurement of what a model can do with each of these outputs. That corpus is this package's test bench too: the text sections were checked against the filing's own text-block facts on all 26 filings, the property graph row for row against the platform's processor, and the JSON importers by round trip.
View & explore
Built holons and TAVI models render in the xbrlkit viewer — the browser side of the toolkit, a reader that renders the financial statements and lets you ask questions of the report with AI:
- Hosted: https://xbrlkit.com/ — open a
holon.jsonldor atavi.jsonand explore the statements, notes and dimensional facts, or chat with the report. - Source: https://github.com/RoboFinSystems/xbrlkit-viewer
The viewer reads a holon entirely client-side, so a single holon.jsonld is a
complete, portable, self-describing report. Its chat asks the report raw
questions (jq over a TAVI model, SPARQL over a holon); xbrlkit serve is the
other side of that pair — the same filing behind shaped tools, on your own
machine.
xbrlkit view joins the two. It resolves a filing the way serve does,
serializes it, and hands that one document to the viewer:
Without installing anything:
A browser cannot be handed a local path — file:// is unreachable from an
https page, and a file input cannot be pre-populated — so this serves the
document instead, on an ephemeral loopback port with an unguessable path, and
opens xbrlkit.com/view?url=… pointing at it (earlier releases open
xbrlkit.com/?url=…, which keeps working). http://127.0.0.1 is a
potentially trustworthy origin, so the https page may read it; the CORS header
names the viewer's origin and no other. The document is readable there, by that
origin, until you press Ctrl-C. --viewer points at a different build.
From an MCP client the same thing is the view_filing tool: "load NVDA",
then "show me it".
License
MIT © 2026 RFS LLC — see LICENSE.
来源:README.md,提交 499687d
工具
0版本历史
17- v0.21.4最新Nov 1, 2026
- v0.21.3Oct 15, 2026
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