原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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Canli Backtest

作者:arhancanli版本 0.6.0i★ –i在你的电脑上运行
注册名称io.github.arhancanli/canli-backtest-mcp

安装

概览

作者提供的说明(英文原文)

Lookahead-free backtests: point-in-time SEC factors, your prices, real costs, every variant counted.

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。

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: 其他

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

  • npm已安装 Node.js(用于 npx 命令)

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": {
    "canli-backtest": {
      "command": "npx",
      "args": [
        "-y",
        "canli-backtest-mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add canli-backtest -- npx -y canli-backtest-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": {
    "canli-backtest": {
      "command": "npx",
      "args": [
        "-y",
        "canli-backtest-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": {
    "canli-backtest": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "canli-backtest-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9日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 arhancanli 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“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 18674 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 18674 个服务器的 99% 更新
  • 基础检查结果等于或优于此分类中其他 18674 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

Canli Backtest 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(0.6.0)于今天进入注册中心。

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 Node.js。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, bot2bot

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:↓ 每周下载量i★ 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

Spec Driven Development

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

作者:formulahendry起步阶段↓ 66/周★ 44014个月前更新

在你的电脑上运行

Remote Desktop Commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

作者:desktop-commander正在增长★ 2114天前更新

在云端运行✓ desktopcommander.app

bot2bot

Let your AI assistant message the bots of family and friends.

作者:bot2bot.link起步阶段今天更新

在云端运行✓ bot2bot.link

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。

canli-backtest-mcp

Backtests an AI agent can trust. An MCP server that builds point-in-time factors from SEC filings, runs cross-sectional backtests of any signal on your own prices with no lookahead (enforced in code), charges costs on the actual trades, and records every variant in a trial ledger, so the best of a search is judged against the whole search instead of alone.

Local stdio only: your prices, signals and ledgers never leave your machine.

[canli-backtest-mcp on canlicapital.com](https://canlicapital.com/mcp-servers/backtest) · All Canli Capital MCP servers. Free, MIT-licensed. For every server behind one install, use canli-mcp.

Why

Three mistakes make most agent-run backtests look better than they are:

  1. Lookahead. Using a number before it was public: an annual figure in January that was filed in February, or a value that was later restated. pit_factor only uses what had been filed with the SEC by each date, as it stood then; backtest_signal only trades on signal rows dated at least lag_days trading days earlier, and stops if anything reaches past that.
  2. Free trading. Ignoring turnover. Positions drift with prices between rebalances, and costs are charged on the trades from those drifted positions to the new targets.
  3. Counting only the winner. An agent tries 200 variants and reports the best. With ledger, every run is recorded (in canli-validation-mcp's hash-chained ledger), and each reply gives the best run's deflated Sharpe after counting all of them, and the Sharpe that luck alone reaches.

Tools

toolwhat it does
list_factorsThe factors pit_factor builds and what each measures.
pit_factorA factor (roa, gross_margin, operating_margin, revenue_growth, asset_growth, accruals, or level: ) for your tickers, monthly, as known on each date. Writes a signal CSV.
backtest_signalRank on the signal, long the top quantile (and short the bottom), rebalance weekly, monthly, quarterly or every N days, with lag_days, cost_bps and an optional ledger.

Breadth lab, sweeps and labelled data

toolwhat it does
price_panelA price, dollar-volume and industry-group panel built from a fund's holdings (IVV for the S&P 500), ready for the tools below
breadth_signalsThe 24 cross-sectional signals the lab builds sleeves from, each with its reference
breadth_bookEvery signal inside every group of names as a sleeve, traded as one netted account: the book's Sharpe after costs, the netting saved, and its effective independent bets; writes the sleeves as a CSV with their specs
breadth_sweepA grid of book settings run in parallel on every core, or as shards other machines run and merge back (inputs, grid, gaps and duplicates checked); the best Sharpe is set against what the best of that many trials reaches by luck, and with split_date the chosen settings are scored after it
effective_betsHow many independent bets a set of return series holds (the participation ratio of their correlations), by series and by family
annotation_packet, annotation_agreement, annotation_goldBlind labelling packets of figures (or of a draft's figures) with guidelines and an answer key; agreement between labellers (Cohen's kappa); and a gold set with its datasheet

Size, crises and cross-validation

A backtest that assumes any size fills at the close flatters itself, so:

  • Size. Give backtest_signal a capital_usd and a dollar_volume_file. An order fills only up to max_participation of recent daily volume (10% unless you say otherwise) and pays square-root impact, with volume and volatility read from the days before each trade. The reply shows the Sharpe at $100k to $1B, and no Sharpe for a size the market could not take. Order-book depth is not modelled: it needs paid data.
  • Crises. Every reply holds the result against named crises, from the dot-com bust to the 2023 bank run. A crisis its dates do not fully cover is listed as untested, never as passed. crisis_replay does this for any returns file.
  • Cross-validation. cpcv takes every variant's returns and, for each choice of held-out blocks, chooses the best on the rest, with purge and embargo at the edges, then scores it on what was held out. You get a spread of out-of-sample results, not one path. Splits can run as shards on other machines and merge back.

A record, a league and a paper market

  • Proof ledger. proof_filings writes what companies filed into an append-only file, each line chained to the last and each batch signed, with a line for every figure a later filing changed. proof_file adds any file's hash, proof_verify checks the whole file and says which line first fails. It shows lines were not altered, not that a figure is right, and no record means only no record. Publish the head somewhere else, or the key holder could rewrite it all. The published ledger does that with a public attestation each month.
  • League. league_new, league_commit and league_score run a tournament scored after the fact: an entrant signs and commits a hash before a round closes and shows the file afterwards, and anyone with the files can rerun the table. Each record is set against the best luck gives across that many entrants. The top entrants, chosen on earlier rounds only, form a paper book. No prizes, no stakes, nobody's money.
  • Arena. arena_new, arena_orders and arena_step are a paper market for agents to trade in, cleared in a call auction, reproducible from a seed. Made-up assets and made-up money: it cannot reach anything real.
  • Agent exchange. exchange_new, exchange_join, exchange_view, exchange_orders, exchange_step and exchange_report are a closed paper market where different AI agents and scripted traders meet in limit order books, with margin rules and forced selling, so a shock can become a cascade. exchange_run runs a whole market of scripted traders in one call. Time moves in steps, each agent sees only its own account, and a hash of the tape lets anyone check a run. Made-up assets and money. The rules are in docs/AGENT_EXCHANGE.md.
  • Consensus. agent_consensus combines agents' probabilities and counts how many independent views they really hold, from how their errors move together: five models that share their mistakes are not five votes.
  • Diversifiers. find_diversifiers ranks candidates by the independent bets they add and how they behave on the book's worst days. Return is shown last and never used to rank.

Quick start

npx -y canli-backtest-mcp

Claude Code:

claude mcp add canli-backtest -- npx -y canli-backtest-mcp

Then ask: *"Build roa for these 200 tickers from 2015 to 2024, backtest it monthly on prices.csv with 10 bps costs, try quantiles 0.1, 0.2 and 0.3 in the ledger 'roa-search', and tell me whether the best one survives the search."*

Files

Both files are CSV with a date column (YYYY-MM-DD) and one column per ticker:

  • prices: closing prices, one row per trading day. Bring your own; adjust for splits and dividends if you want total returns. The server does not supply prices (vendor licences forbid passing them on).
  • signal: one row per date the values became known. pit_factor writes this; your own signal works too, as long as each row is dated by when it was available.

Empty cells are missing values, never zero.

What a result does not establish

  • Prices are yours: survivorship, splits, dividends and data errors in them pass straight into the result.
  • A backtest measures one path of history under these costs; it does not establish that the signal keeps working.
  • Costs are a flat rate per unit traded; market impact, short-borrow fees and financing are not charged unless included in cost_bps.
  • SEC values are what companies reported in XBRL, as filed; late filers, non-XBRL filers and tag changes can be missing.

Configuration

variabledefaultmeaning
CANLI_LEDGER_DIR~/.canli/ledgerswhere ledgers are kept (shared with canli-validation-mcp)
CANLI_CACHE_DIR~/.cache/canli-fundamentalsSEC data cache

Part of the Canli Capital MCP family

canli-validation-mcp (validators and the trial ledger), canli-fundamentals-mcp (SEC fundamentals point in time), canli-research-mcp (the open research record). Source: github.com/arhancanli/canlicapital. MIT licensed. Built by Arhan Canli.

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