Okama MCP

Name: Okama MCP
Author: mbk-dev

作者：mbk-dev版本 3.1.0i★ –i在你的电脑上运行

注册名称io.github.mbk-dev/okama-mcp

安装

概览

作者提供的说明（英文原文）

Portfolio analytics via the okama library: backtests, Monte Carlo, efficient frontier, PNG charts

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。

用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
我们的基础检查i1 项中通过 1 项依据公开信息检查；尚未扫描代码
使用情况i尚未统计★ –

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: 在你的电脑上运行
传输方式: stdio
分类: 营销与社交媒体

安装

选择你使用的 AI 应用，然后复制设置。

安装之前

基础检查：1 项中通过 1 项
在你的电脑上运行，拥有你的用户账户的权限（文件、网络、应用）。
注册中心没有列出需要填写的密钥。

你需要

PyPI已安装 Python 的 uv（用于 uvx 命令）

你用的是哪个应用？

ClaudeClaude CodeCursorVS CodeChatGPT

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 …”。

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

{
  "mcpServers": {
    "okama": {
      "command": "uvx",
      "args": [
        "okama-mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add okama -- uvx okama-mcp

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": {
    "okama": {
      "command": "uvx",
      "args": [
        "okama-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。

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": {
    "okama": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "okama-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。

这个服务器在你的电脑上运行，而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

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。

它能做什么

它在你的电脑上运行；安装后，工具列表会显示在你的 AI 应用中。

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7日

✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 mbk-dev 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
– 不适用
端点有响应
它在你的电脑上运行，没有互联网端点
– 不适用
使用 OAuth 登录
在你的电脑上运行，改用本地设置
… 尚未检查
工具描述中没有隐藏指令
它在你的电脑上运行；我们只能读取互联网端点的工具列表

与“营销与社交媒体”中的其他服务器比较i

星标数多于此分类中其他 2980 个服务器的 0%
发布到注册中心的时间比此分类中其他 2980 个服务器的 75% 更新
基础检查结果等于或优于此分类中其他 2980 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

Okama MCP 安全吗？

它在 1 项适用的基础检查中通过了 1 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？

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。

它在我的电脑上运行还是在云端？

它在你的电脑上运行。你的 AI 应用会在需要时启动它，数据不会经过作者的服务器（除非它自己调用在线服务）。

它还在维护吗？

GitHub 仓库最后更新于–，最新版本（3.1.0）于11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。你的电脑上还需要有 Python (uv)。

有什么可以替代它？

同一分类中有：MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

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：★ 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 YouTube Transcript

作者：jkawamoto

An MCP server retrieving transcripts of YouTube videos

在你的电脑上运行★ 495MIT10天前更新

安装

Google Analytics MCP

作者：surendranb

GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.

在你的电脑上运行★ 244MIT10天前更新

安装

BibiGPT YouTube Video Summarizer

作者：JimmyLv

AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.

在云端运行★ 137MIT10天前更新

安装

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。

okama-mcp

MCP (Model Context Protocol) server that exposes the okama investment portfolio toolkit and okama Planner to AI assistants — Claude Desktop, Claude Code, Cursor, Codex, and any other MCP-compatible client.

With okama-mcp installed, you can ask an AI things like:

*"Backtest a portfolio of 30% gold and 70% real estate over the last 15 years."*

*"Run a Monte Carlo retirement forecast on that portfolio, withdrawing $1,000/month

indexed to inflation, over 25 years."*

*"What's the tangency portfolio of SPY, BND, and GLD with a 3% risk-free rate?"*

…and the AI uses the MCP tools to call okama directly — no Python code needed.

Built on FastMCP. Single codebase, two transports: stdio (for local clients) and streamable-http (for self-hosting). okama-mcp is free and open source. Run it locally or on your own server. The HTTP transport is intended for self-hosting; mcp.okama.io serves the project landing page, not a public MCP endpoint. Client registry tools and Excel exports require a compatible Planner companion and a configured local stdio installation.

Install

Development status (26 October 2026): main prepares MCP 3.1.0 with Planner 0.5.0; neither version has been published yet. Use the source setup below. PyPI still provides MCP 3.0.0 with Planner 0.4.1 and its earlier contracts.

Requires Python ≥ 3.11 (same floor as okama itself); okama ≥ 4.0.0 and okama-planner[reports]>=0.5.0,<0.6.0 are required.

Client data modes (source checkout): local MCP defaults to anonymous reads. client_data_mode_set({"mode":"personal_data"}) enables full client CRUD; {"mode":"anonymous"} disables client writes again. The setting persists per database across connections. uv sync installs a pinned Planner 0.5.0 source revision with the required access API. PyPI still provides Planner 0.4.1, so the prepared release remains blocked until the compatible companion is published; see installation and release gates. Market and finplan_* tools remain available independently. See the 3.0 migration notes for the earlier release behavior.

The easiest way — no clone, no venv — is uv or pipx:

uvx okama-mcp stdio          # run straight from PyPI

or

pipx install okama-mcp

Plain pip works too:

pip install okama-mcp

[!WARNING]

With pip, prefer a dedicated virtual environment: on most modern Linux distros the

system Python is marked externally managed (PEP 668), so pip install outside a venv

fails, and a shared environment risks dependency conflicts. In your MCP client config,

point command at the absolute path of the okama-mcp script inside the venv — GUI

clients don't see your shell PATH. uvx and pipx avoid all of this by isolating

the install automatically.

To work on the code, install from source instead:

git clone https://github.com/mbk-dev/okama-mcp

cd okama-mcp uv python install 3.14 uv sync --python 3.14 --all-groups

Until Planner 0.5.0 is published, tool.uv.sources pins an immutable development companion. Release gates use uv sync --all-groups --no-sources and require published dependencies; no source substitution is used for publication. Remove the development pin after published-pair acceptance passes.

Run

# stdio — for Claude Desktop, Claude Code, Cursor (local IPC)

okama-mcp stdio

streamable HTTP — for self-hosting on your own server

okama-mcp http --host 127.0.0.1 --port 8765

When running from a source checkout, prefix each command with uv run. Each worktree has its own .venv; test and dev groups are installed by default. uv.lock is generated locally and is not committed, so fresh checkouts resolve compatible versions independently. Orca runs the bootstrap in orca.yaml before starting the agent; its source MCP configuration uses uv run --no-sync after setup.

Connect a client

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

"mcpServers": { "okama": { "command": "uvx", "args": ["okama-mcp", "stdio"] } } }

Restart Claude Desktop; the server appears in the tools menu.

Claude Code

To make the server available in every project (works from any directory):

claude mcp add --scope user okama -- uvx okama-mcp stdio

Developers running from a source checkout can use claude mcp add okama -- uv run okama-mcp stdio from the project root instead.

Or commit a .mcp.json at the project root so the whole team picks it up:

"mcpServers": { "okama": { "command": "uvx", "args": ["okama-mcp", "stdio"] } } }

Cursor

Add the server to .cursor/mcp.json in your project (or ~/.cursor/mcp.json to make it global):

"mcpServers": { "okama": { "command": "uvx", "args": ["okama-mcp", "stdio"] } } }

Codex (CLI & Desktop)

Add the server with one command:

codex mcp add okama -- uvx okama-mcp stdio

Or declare it in ~/.codex/config.toml (or a project-scoped .codex/config.toml in trusted projects):

[mcp_servers.okama]

command = "uvx" args = ["okama-mcp", "stdio"]

The Codex CLI, desktop app, and IDE extension share this configuration — set it up once and it works in all three.

Self-hosting (streamable HTTP)

Run okama-mcp on your own server and share it across your MCP clients:

okama-mcp http --host 127.0.0.1 --port 8765 --path /mcp

(From source: uv run okama-mcp http ...)

Then point your MCP client at http:// :8765/mcp. For a production setup put nginx + TLS in front; ready-made examples live in deploy/:

deploy/systemd/okama-mcp.service — systemd unit (hardened, runs as a dedicated user)
deploy/nginx/self-hosted.conf — nginx vhost: TLS, SSE-friendly proxying of /mcp

The server is open by design — free to run, no registration. If your instance must not be public, restrict access at the nginx level (allow-list, VPN, or HTTP basic auth).

Tool catalog

A multi-stage financial plan (contribute $1,000/month for 20 years into a 70/30 SPY/AGG portfolio, then withdraw $6,000/month indexed to inflation for 25 years), a Monte Carlo retirement forecast (30% gold / 70% real estate, withdrawing $1,000/month indexed to inflation over 25 years) and the efficient frontier of SPY/BND/GLD:

Financial tools are stateless — pass the full portfolio specification with every call. Optional local client tools use stable registry codes and a persistent, database-scoped access mode. Client creation is not idempotent: inspect the registry before retrying an ambiguous creation result. The server caches expensive okama objects (Portfolio, EfficientFrontier) by content hash, so repeated calls on the same spec are fast.

Nested portfolios. Wherever a list of assets is accepted — the assets field of PortfolioSpec/FrontierSpec, or the portfolios argument on the comparison tools — an entry may be a ticker string or a nested portfolio object (the same spec shape). This lets you treat a whole portfolio as a single component: e.g. compare a 60/40 portfolio against gold, or put a sub-portfolio on the efficient frontier.

Search & metadata

Tool	Purpose
`search_assets(query="", namespace?, asset_type?, oldest_first?, limit=50, offset=0)`	Search by name / local name / ticker / ISIN, with exact identifiers and names ranked first; follow `next_offset` while `has_more` is true. Filter by okama type and sort by `first_date`; for example, `namespace="MOEX", asset_type="ETF", oldest_first=true, limit=5` finds the five oldest MOEX-listed BPIFs.
`list_namespaces(kind="all"\	"assets"\	"macro")`	Show namespace descriptions plus `usage`: asset/macro classification, support for asset returns, and available MCP tools.
`get_asset_info(symbol)`	Metadata for one symbol — name, country, currency, type, date range.

Single asset & comparisons

Tool	Purpose
`get_asset_history(symbol, kind, first_date?, last_date?)`	Time series for one asset. `kind` ∈ {`close_monthly`, `close_daily`, `adj_close`, `ror`, `dividends`}.
`compare_assets(symbols, ccy, ..., portfolios?, rf_return?, t_return?)`	Side-by-side statistics (`describe()` table: CAGR, risk, drawdowns by period) plus Sharpe & Sortino per asset.
`get_correlations(symbols, ccy, ..., portfolios?)`	Correlation matrix of monthly returns.
`get_rolling_risk(symbols, ccy, window_months=12, ..., portfolios?)`	Rolling annualized risk per asset.
`get_asset_returns(symbols, ccy, ..., portfolios?, period?, real=False)`	Return metrics per asset: CAGR, cumulative return, mean / real mean return, monthly geometric mean, annual returns table. With `inflation=False`, nominal metrics remain available and `real_mean_return` is `null`; `real=True` requires `inflation=True`.
`get_rolling_returns(symbols, ccy, window_months=12, real=False, ..., portfolios?)`	Rolling CAGR and rolling cumulative return per asset.
`get_benchmark_metrics(benchmark, symbols, ccy, ..., portfolios?, rolling_window?)`	Beta, correlation, annualized tracking difference and tracking error of each asset vs a benchmark/index.
`get_dividend_info(symbols, ccy, ...)`	LTM dividend yield, 5y mean yield, paying/growing streaks per asset.

Portfolio backtest

Tool	Purpose
`analyze_portfolio(portfolio, rf_return=0, t_return=0)`	Headline metrics (CAGR, annual mean/risk, Sharpe, Sortino) + full `describe()` for a `PortfolioSpec`.
`get_portfolio_drawdowns(portfolio)`	Drawdown time series + max drawdown / recovery period.
`get_portfolio_var_cvar(portfolio, time_frame=12, level=1)`	Historical Value at Risk and CVaR.
`get_portfolio_wealth_index(portfolio, full=False)`	Wealth-index series (cumulative growth of 1000).
`get_rolling_cagr(portfolio, window_months=12, real=False)`	Rolling CAGR time series (optionally inflation-adjusted).
`get_cagr_probability(portfolio, years, cagr_target)`	Historical probability of CAGR below a target (e.g. of a loss) over N-year periods.

Monte Carlo DCF

Tool	Purpose
`monte_carlo_forecast(portfolio, mc, cashflow)`	Forward simulation with one of five cash-flow strategies (`indexation`, `percentage`, `time_series`, `vanguard`, `cut_if_drawdown`). Returns percentile wealth bands, terminal-wealth stats, survival metrics. Includes the money-weighted IRR distribution (percentiles + mean).
`get_portfolio_irr(portfolio, cashflow)`	Historical money-weighted return (IRR) for a contribution/withdrawal plan.

| `find_the_largest_withdrawa

只显示了开头部分；其余内容请在仓库中阅读

Okama MCP

概览

PopNx MCP 的三大支柱

它能帮你做什么

安装

安装之前

它能做什么

基础检查i

作者与仓库一致

仍在维护

有许可证

端点有响应

使用 OAuth 登录

工具描述中没有隐藏指令

与“营销与社交媒体”中的其他服务器比较i

常见问题

替代选择

MCP YouTube Transcript

Google Analytics MCP

BibiGPT YouTube Video Summarizer

作者的 README

okama-mcp

Install

or

Run

streamable HTTP — for self-hosting on your own server

Connect a client

Claude Desktop

Claude Code

Cursor

Codex (CLI & Desktop)

Self-hosting (streamable HTTP)

Tool catalog

Search & metadata

Single asset & comparisons

Portfolio backtest

Monte Carlo DCF