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)
Lookahead-free backtests: point-in-time SEC factors, your prices, real costs, every variant counted.
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": {
"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。
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9日
注册名称已通过 GitHub 账户 arhancanli 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(0.6.0)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。你的电脑上还需要有 Node.js。
同一分类中有:Spec Driven Development, Remote Desktop Commander, bot2bot
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
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.
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。
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.
Three mistakes make most agent-run backtests look better than they are:
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.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.| tool | what it does |
|---|---|
list_factors | The factors pit_factor builds and what each measures. |
pit_factor | A 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_signal | Rank 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. |
| tool | what it does |
|---|---|
price_panel | A 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_signals | The 24 cross-sectional signals the lab builds sleeves from, each with its reference |
breadth_book | Every 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_sweep | A 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_bets | How 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_gold | Blind 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 |
A backtest that assumes any size fills at the close flatters itself, so:
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.crisis_replay does this for any returns file.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.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_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_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.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.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.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.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."*
Both files are CSV with a date column (YYYY-MM-DD) and one column per ticker:
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.
cost_bps.| variable | default | meaning |
|---|---|---|
CANLI_LEDGER_DIR | ~/.canli/ledgers | where ledgers are kept (shared with canli-validation-mcp) |
CANLI_CACHE_DIR | ~/.cache/canli-fundamentals | SEC data cache |
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.