Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Point-in-time, survivorship-free SEC EDGAR fundamentals + smart-money signals for AI agents.
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。
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。
选择你使用的 AI 应用,然后复制设置。
你需要
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:
https://mcp.valuein.biz/mcp在终端中运行这条命令
claude mcp add --transport http sec-edgar https://mcp.valuein.biz/mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"sec-edgar": {
"url": "https://mcp.valuein.biz/mcp"
}
}
}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。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"sec-edgar": {
"type": "http",
"url": "https://mcp.valuein.biz/mcp"
}
}
}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:
https://mcp.valuein.biz/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。
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。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
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7日
注册名称已通过 GitHub 账户 valuein 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
在 438 毫秒内响应(HTTP 200)
无需登录
尚未检查;我们会在检查端点时读取工具列表
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。
它在 2 项适用的基础检查中通过了 2 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。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(3.17.0)于今天进入注册中心。
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。
同一分类中有:Spec Driven Development, Remote Desktop Commander, Microsoft Exchange Online MCP
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ 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
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Exchange Online admin for MSPs: forwarding audits, EWS posture and offboarding, no PowerShell
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。
Point-in-time, survivorship-free SEC fundamentals — built for AI agents, safe enough for institutions that fear AI. Every number is born in a filing and carries a
fact_id; the model never mints a digit. Streamed as Parquet, queried with DuckDB or natural language, reproducible run to run.
This repository is the public home and discovery hub for the Valuein data platform. It hosts the documentation, examples, notebooks, and the MCP registry manifest used by AI agents to find us. Source code for the SDK, MCP server, and data pipeline lives in dedicated repositories — this is the front door.
pip install "valuein-sdk>=7.1.0" # data for code
| You want to… | Go to |
|---|---|
| Try the SDK in 30 seconds without a token | Quickstart |
| See every channel we ship through | Distribution channels |
| Check pricing and what each plan unlocks | Plans & access |
| See why AI agents are first-class citizens here | Built for AI agents |
| Connect an AI agent (Claude, Copilot, ChatGPT, Cursor…) | MCP for AI agents |
| Set up the Workspace by role (analyst, PM, quant, creator) | docs/WORKSPACE_GUIDE.md |
| Read the data model | Data model |
| Find a quick recipe by role | Recipes by role |
| Run end-to-end Python examples | examples/python/ |
| Run interactive notebooks (Colab) | examples/notebooks/ |
| Read the methodology / SLA / compliance | Documentation |
| Report a data error or request a feature | Support & community |
| Contribute an example or notebook | CONTRIBUTING.md |
Survivorship-bias-free, point-in-time US fundamentals sourced directly from SEC EDGAR.
'Other' rather than droppedfiling_date and millisecond-precision accepted_atCounts move with every snapshot, so this page does not copy them; read them live. client.manifest() returns the snapshot id, last_updated and your plan's tables; curl -s https://data.valuein.biz/v1/sample/manifest.json | jq .schema_version prints the live schema version; https://data.valuein.biz/v1/plans gives each plan's universe size and history window; docs/data_catalog.md lists the canonical concepts and ratios.
| Property | What it means for you |
|---|---|
| 🕒 Point-in-time | filing_date <= trade_date removes look-ahead bias. accepted_at gives intraday resolution for same-day signals. |
| ⚖️ Survivorship-bias free | Delisted, bankrupt, and acquired companies remain in every snapshot — your backtest sees the universe the market saw. |
| 📊 Standardized concepts | Both the raw XBRL tag (fact.concept) and the canonical name (fact.standard_concept) are on every row. No hidden mapping table. |
| 🔍 CPA-verified catalog | Every standard_concept carries a review_confidence — 1.0 once an accountant has signed off on its name, statement and rule (then it's locked; the pipeline only ever adds new concepts, never mutates a verified one), 0.7 while provisional. Filter review_confidence >= 1.0 for the labels analysts, quants and AI models can agree on and train against. |
| 🚀 DuckDB-native | Millisecond analytics over remote Parquet via httpfs. Zero database provisioning. |
| 🔁 Append-only restatements | A 10-K/A adds a new row — the original stays. Reconstruct the as-reported view of any historical date. |
| 🧾 Measured, published accuracy | Mathematical consistency checked against published, cited accounting identities — CI-gated, and re-derivable yourself with one DuckDB command. The current measured figure lives in docs/accuracy/baseline.json. |
| 🔐 One token, every channel | The same Bearer token authenticates the SDK, MCP server, and bulk-data API. |
Valuein is MCP-first and agent-agnostic: the same typed tool surface works in Claude, Copilot, ChatGPT, Perplexity, Gemini, Grok, Cursor, or your own LangGraph / CrewAI agent. The design goal is simple — the model never mints a number. Numbers are born in tools, carried as provenance-tagged facts, and the model is only allowed to arrange words around figures it was handed.
| Guarantee | How it's enforced |
|---|---|
| Fact-level lineage | Every figure a tool returns carries a fact_id and its source filing; verify_fact_lineage round-trips any fact_id back to the exact SEC filing URL in one call. |
| Zero look-ahead | Every time-series tool accepts as_of_date and reconstructs the information set as of that date — the same PIT discipline the Parquet layer enforces for backtests. |
| Reproducible runs | Deterministic, idempotent tools: same inputs, same output. No rolling windows, no hidden "latest". Agents can cache, retry, and replay; you can reproduce a run later. |
| Agent-agnostic state | Theses, claims, watchlists, signals, and reports persist server-side across sessions *and across clients* — save a thesis from Claude today, list it from Cursor tomorrow. |
| Human-on-the-loop (HOTL) | Mutating and outward-facing tool actions go through a staged-action approval ledger: the agent proposes, a human approves, and the decision lands in an immutable audit entry. Read-only tools never stage. |
| Governed managed runs | Server-side managed agent runs execute at temperature 0 with a model allow-list and destructive-tool stripping — reproducible research, not improvisation. |
| Graded track records | Saved theses and claims are scored against subsequent fundamentals and prices; publishing builds a public, verifiable track record — your agent keeps score. |
The full tool reference is in docs/MCP_TOOLS.md; agent-facing runtime instructions are in AGENTS.md.
The same dataset, delivered four ways so it lands where you already work.
| Channel | Audience | Endpoint / install |
|---|---|---|
| Python SDK | Quants, engineers, data scientists | pip install valuein-sdk · PyPI |
| MCP server | AI agents (Claude, Copilot, ChatGPT, Cursor, custom) | https://mcp.valuein.biz/mcp · server.json |
| Web dashboard | Retail, executives, non-technical users | valuein.biz |
| Bulk data API | B2B partners, fintech platforms | https://data.valuein.biz · contact us |
A single Stripe-issued token unlocks every channel at your tier — no per-channel billing.
Pricing and feature scope are mirrored from valuein.biz/pricing — the website is the source of truth and our checkout flow routes to the correct Stripe product.
| Plan | Universe | History | Get it |
|---|---|---|---|
| Sample | Every S&P 500 member since 1996, former members included | 5 calendar years + YTD | Free, no signup: pip install "valuein-sdk>=7.1.0" |
| Benchmark | Every S&P 500 member since 1996, former members included | Full history | Free, register |
| Pro | Full active + delisted universe incl. foreign issuers (20-F, 40-F), fundamentals dataset | Rolling point-in-time window | Subscribe |
| Institutional | Same universe + smart-money dataset (insider transactions on Forms 3/4/5/144 + institutional ownership on Forms 13F/13D/13G) | Full history back to 1993 | Subscribe |
| Enterprise | Organisations and teams, by Enterprise Agreement: the whole dataset, multi-seat · display in your own products and client deliverables, with attribution, where the Order Form says so · dedicated infrastructure · negotiated scope | Custom | sales@valuein.biz |
Redistribution, resale and white-label are not part of any plan, Enterprise included: data vendors and platforms sign a separate Redistribution Licence (sales@valuein.biz).
Prices, universe sizes, history windows and rate limits are served live; read them instead of a copy:
curl -s https://data.valuein.biz/v1/plans \
| jq '.plans[] | {displayName, priceUsd, universeSize, earliestYear, perMinute, perHour}'
Each tier removes a *different* buyer objection — Pro removes the universe + history limits on the fundamentals dataset; Institutional adds the smart-money dataset (insider transactions + institutional ownership), unlimited history back to 1993, filing-event webhooks, and a single-seat internal-use licence (no redistribution); Enterprise is for organisations and teams: an Enterprise Agreement for multi-seat use and, where the Order Form says so, display in your own products and client deliverables with attribution, plus dedicated infrastructure, service levels and bespoke contracts. Redistribution, resale and white-label need a separate Redistribution Licence, which no plan includes.
Subscribe for the data. Pay only for the AI you use.
Autonomous AI agents that hit a rate or tier limit can pay per reque
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