Financial Modeling Prep (fmpsdk)

io.github.daxm由 GitHub 账号 daxm 发布v20260829.1更新于 Oct 24, 2026

Financial Modeling Prep API as MCP tools — quotes, statements, prices, and ~240 endpoints.

已验证STDIO仅桌面金融数据与分析

概览

AI 生成的概览

本地 MCP 服务器,通过精选工具和约 240 个接口的发现能力,让助手查询 Financial Modeling Prep 的市场与公司数据。

可以做什么
查询股票代码的行情、公司概况、财务报表、比率与历史价格,以及市场新闻等 FMP 数据。使用精选工具处理常见请求,并通过发现工具在运行时访问全部约 240 个方法。返回结果通常是字典列表,需要助手自行解析。
适用场景
当助手需要通过已有的 Financial Modeling Prep 订阅获取公司或市场的实时与历史财务数据(基本面、报表、行情、价格图表或新闻)时适用。
运行要求
作为本地进程运行,通常用 uvx 从 PyPI 包 fmpsdk-mcp 启动,需要 Python 3.9 及以上。需要以环境变量 FMP_API_KEY 提供 Financial Modeling Prep API 密钥,并需要访问 FMP 的网络连接。许多接口需要付费的 FMP 套餐等级。
安装前请注意
FMP_API_KEY 凭据会传给本地进程,请勿放入共享配置。接口受 FMP 套餐等级限制,未覆盖时会抛出套餐限制错误;TipRanks 方法需要单独付费附加包,且未针对真实响应验证。数据会发送到 FMP 的服务器。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Financial Modeling Prep (fmpsdk),将其添加到工作区。
  2. 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

FMP SDK

[PyPI version] [Python versions] [License: BSD-3-Clause]

The idea behind this project is to provide a 'one-stop-shop' to the API endpoints provided by Financial Modeling Prep (FMP).

A personal note to you: my apologies for letting this package get so out of date. FMP kept reshuffling its API, then I had a personal issue delay me further. Things are back on track now. Because of that gap, roughly half of this package's old methods had gone defunct against FMP's current API, so rather than patch around that I rebuilt it from scratch against FMP's stable/ API. If you're on 20250102.0 or earlier you're on the old, pre-rewrite methods; anything newer uses the schema described below. Old releases are yanked from PyPI (a plain pip install fmpsdk now always gets the rewrite), but still installable if you pin one explicitly, e.g. pip install fmpsdk==20250102.0 — note that won't actually restore functionality, though: FMP sunset the legacy /api/v3/ API those old methods called entirely on 2025-08-31, so a pinned old version installs fine but its calls will fail regardless. It's there for compatibility with existing pinned requirements files while you migrate, not as a way to keep avoiding the rewrite.

What's covered

29 data groups, ~240 methods total, each reachable both as client.<method>(...) and grouped under a matching namespace, e.g. client.statements.income_statement(...):

  • Company & fundamentals — profile, executives, M&A, DCF valuation, financial statements/ ratios/growth (income, balance sheet, cash flow — as-reported, TTM, and growth variants)
  • Market data — real-time & aftermarket quotes, historical price charts, technical indicators
  • Reference & screening — symbol/CIK/CUSIP/ISIN search, the company screener, sector/ industry/exchange directories
  • Calendars & events — earnings, dividends, splits, IPOs, the economic calendar
  • Ownership & compliance — insider trades, Form 13F institutional ownership, SEC filings, ESG disclosures
  • Alternative markets — crypto, forex, commodities, indexes, ETFs & mutual funds
  • Sentiment & analysis — analyst grades/price targets, TipRanks ratings, congressional trading, market movers
  • Bulk downloads — whole-universe data dumps, one call instead of one per symbol

Every method's own docstring says which FMP plan tier it needs (Free/Starter/Premium/ Ultimate) — see Pricing tiers below. One exception: the 7 client.tipranks methods are implemented and unit-tested but untested against a real response — see that section for why.

How to Use

  1. Requires Python 3.9+. Install the package: pip install fmpsdk python-dotenv (python-dotenv is optional — it's just how the example below loads your API key from a .env file).
  2. Create a .env file and put your API key in it. Inside .env: FMP_API_KEY='blah'
  3. Build a Client and call methods on it, grouped by data category — e.g. client.company.profile(symbol="AAPL"), client.statements.income_statement(symbol="AAPL").
  4. The return from a method call is almost always a list of dictionaries. It is up to you to parse it.

Example code

python
#!/usr/bin/env python3
from dotenv import load_dotenv
import fmpsdk
# Actual API key is stored in a .env file. Not good to store API key directly in script.load_dotenv()client = fmpsdk.Client()  # reads FMP_API_KEY from the environment
# Company Valuation Methodssymbol = "AAPL"print(f"Company Profile: {client.company.profile(symbol=symbol)}")
# Every non-2xx FMP response raises a typed exception instead of returning# None or an error-shaped dict, so a plan-gated or bad-key call is obvious:try:    client.statements.income_statement_ttm(symbol=symbol)except fmpsdk.FMPPlanLimitError:    print("Your FMP plan doesn't cover this endpoint — check its docstring for which tier does.")except fmpsdk.FMPAuthenticationError:    print("Check your FMP_API_KEY.")

One naming quirk worth knowing up front: client.quote is the namespace for the whole quote group (client.quote.aftermarket_quote(...), client.quote.batch_quote(...), etc.), so it shadows the top-level quote() method of the same name — call that one as client.quote.quote(symbol="AAPL").

Pricing tiers

FMP's plans form a ladder — Free, Starter, Premium, Ultimate — and each one adds more endpoints on top of the last. A call your plan doesn't cover raises fmpsdk.FMPPlanLimitError rather than returning data. There's no single tier table to keep in sync here — instead, every group module's docstring (e.g. fmpsdk/endpoints/search.py) and every method's own docstring says plainly which tier it needs, right next to the code that calls it, verified live against a real key at every tier from Free through Ultimate. Check those, or just try the call and catch FMPPlanLimitError.

One exception, outside that ladder entirely: client.tipranks's 7 methods. They still 402 even on Ultimate — FMP's own error message says why: TipRanks data needs a separate paid add-on ("TipRanks data boost"), bought independently of the four plan tiers above. We haven't purchased it, so these 7 methods are implemented and unit-tested (mocked) but never verified against a real response — treat them as unverified rather than confirmed-working. If you have that add-on and hit a bug in one of them, a PR with the fix (and what the real response actually looks like) is welcome.

MCP server & OpenAPI spec

mcp/ — a Model Context Protocol server, published separately as fmpsdk-mcp (so pip install fmpsdk never pulls in fastmcp). Lets an AI assistant (Claude Code, Claude Desktop, …) query FMP through this library: 10 curated tools for the common asks (quotes, profiles, statements, ratios, price history, news) plus discovery tools that reach all ~240 methods at runtime. With uv:

bash
claude mcp add fmpsdk -s user -e FMP_API_KEY=your-key -- uvx fmpsdk-mcp

See mcp/README.md for the Claude Desktop config, the full tool list, and development setup.

openapi.json — an OpenAPI 3.1 description of the same API surface. FMP publishes no OpenAPI/Swagger document; this file is generated by introspecting this library's source (python tools/gen_openapi.py), not fetched from or endorsed by FMP.

Contributing

See CONTRIBUTING.md — dev setup, the unit/live/ultimate test tiers, and specifically how to verify and PR a fix for the untested tipranks methods above.

License

BSD 3-Clause — see LICENSE.md.

Attribution

Special thanks to the following people who have pitched in on this project! Open source works thanks to people who jump in and help! These are this project's stars. Thank you.

来源:README.md,提交 3f9f68b

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v20260829.1最新Sep 16, 2026

评分

已满足适用检查项的 50%

该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。

  • 近 30 天内可连通25 分

    请保持端点能够响应 MCP 握手;SourceWeft 每 30 天探测一次。

  • 已声明认证方式10 分

    请在注册中心条目中声明凭据请求头,或保持端点能够响应探测,以便判定其认证方式。

  • 已列出工具15 分

    请让服务器在无凭据时响应 tools/list,或发布可在沙箱中无凭据启动的软件包。

  • 描述必需15 分
  • 图标10 分
  • 文档15 分
  • 许可证10 分