Finance Toolkit
500+ transparent financial methods calculated from raw statements, not third-party endpoints.
作者提供的说明(英文原文)
Risk guardrails for AI trading agents. Your agent proposes; your policy decides.
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 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"agentrisk": {
"command": "uvx",
"args": [
"agentrisk"
]
}
}
}在终端中运行这条命令
claude mcp add agentrisk -- uvx agentrisk粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"agentrisk": {
"command": "uvx",
"args": [
"agentrisk"
]
}
}
}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": {
"agentrisk": {
"type": "stdio",
"command": "uvx",
"args": [
"agentrisk"
]
}
}
}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。
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 trycoin-ai 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
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
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 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。
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)。
GitHub 仓库最后更新于–,最新版本(0.1.3)于40天前进入注册中心。
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)。
同一分类中有:Finance Toolkit, SolidInvoice, Korea Tax Calculator
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
500+ transparent financial methods calculated from raw statements, not third-party endpoints.
Create and send invoices and quotes, manage clients, and track payments in SolidInvoice.
Korean tax calculation and tax-audit judgment MCP: 96 tools with statutory citations.
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。
Risk guardrails for AI trading agents. Your agent proposes; your policy decides.
AgentRisk sits in front of trade execution: it analyzes portfolio risk, checks each proposed trade against a policy you write, and manages that policy. The core is deterministic (same inputs, same verdict), transparent (policies are plain YAML you can read and edit), and fail-closed (invalid input or a missing policy blocks, never a silent pass).
AgentRisk never recommends trades and never executes them. A
PASSmeans a trade
did not break the rules *you* wrote, not that it is safe or profitable. See
DISCLAIMER.md.
The fastest path for a Claude agent is the Claude Code plugin. It installs the Agent Skill and registers the MCP server in one step (via uvx, so there is nothing else to install):
/plugin marketplace add trycoin-ai/agentrisk
/plugin install agentrisk@agentrisk
For any other MCP client, register the server yourself:
{
"mcpServers": { "agentrisk": { "command": "uvx", "args": ["--from", "agentrisk[mcp]", "agentrisk-mcp"] } } }
Then ask questions in plain English and the agent translates them into three tool calls:
| Tool | Question it answers | Returns |
|---|---|---|
analyze_portfolio_risk | What risk am I holding? | Concentration, exposure, and policy-compliance report |
check_trade_risk | Should this trade go through? | PASS / WARN / BLOCK with a one-line reason |
generate_risk_policy | What are my rules? | A human-readable YAML policy (create, update, show) |
The plugin path needs uv for uvx. See examples/claude_desktop.md for a two-minute Claude Desktop setup.
For Claude agents, AgentRisk ships an optional Agent Skill that encodes the discipline the guardrail depends on: before any order reaches a broker, classify the trade, call check_trade_risk, respect the verdict, and record the result, in that order. The plugin above installs it with the server. To install just the skill:
skills/agentrisk/ into ~/.claude/skills/.skills/agentrisk/SKILL.md as a skill.AgentRisk returns advice. It cannot physically stop an order, so your integration must gate execution on the verdict:
result = check_trade_risk(portfolio, trade)
if not result.proceed: refuse(result.summary) # BLOCK: never call the broker elif result.acknowledgements_required: confirm_with_user(result) # WARN: surface warnings first else: execute(trade) # PASS
If you call the broker regardless of the verdict, you have a logger, not a guardrail. See the integration guide.
The three tools are also a pure Python library, with no network calls and no LLM in the core:
pip install agentrisk
Every parameter, return field, and error case is in the tool reference.
The policy reference covers every field and the safety behaviors: fail closed, exits are never trapped, only breach-worsening trades block, and the one-time bypass.
| Doc | Contents |
|---|---|
| Concepts | The mental model and the agent/AgentRisk division of labor |
| Architecture | The module layout and how a call flows through the core |
| Policy reference | Every policy field and the check behavior it drives |
| Tool reference | Parameters, outputs, and error cases for all three tools |
| CLI reference | The agentrisk command: policy, check, analyze |
| Integration guide | The enforcement contract, broker MCP pairing, audit log |
| Threat model | What AgentRisk can and cannot protect against |
| Classification data | The open taxonomy and how to contribute corrections |
Next is deterministic stress scenarios, ETF look-through, and behavioral limits (v0.2), then options analytics, broker snapshot adapters, short positions, and multi-currency (v0.3). Trade recommendations, signals, execution, and telemetry are permanently out of scope. See the milestones.
Classification-data corrections and new deterministic checks are especially welcome. See CONTRIBUTING.md, and keep the core pure: no network, no LLM calls, no hidden state.
MIT. See LICENSE.