Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者による説明(英語の原文)
Analytical engine for US-listed equities: screens, rankings, and event studies in plain English.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
ウェブ、デスクトップ、モバイルのClaudeで使えます:
https://mcp.mrmarket.ai/mcpターミナルでこれを実行します
claude mcp add --transport http mrmarket https://mcp.mrmarket.ai/mcpプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"mrmarket": {
"url": "https://mcp.mrmarket.ai/mcp"
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"mrmarket": {
"type": "http",
"url": "https://mcp.mrmarket.ai/mcp"
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
ChatGPTがつなげるのは、インターネット上のサーバーだけです:
https://mcp.mrmarket.ai/mcpメニューの名前は、プランや時期によって少し違うことがあります。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
このサーバーのツール一覧はまだ読み取っていません。エンドポイントは順番にチェックしています。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月7日にチェック
レジストリ名はドメイン mrmarket.ai で確認済みです(レジストリがドメインの所有を確認しています)
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
まだチェックしていません。エンドポイントは順番にチェックしています
まだチェックしていません。エンドポイントは順番にチェックしています
まだチェックしていません。エンドポイントをチェックするときにツール一覧を読み取ります
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
作者のクラウドで動きます。インストール不要でインターネット経由でつながりますが、送った内容は作者のサーバーを通ります。
GitHubリポジトリの最終更新は–、最新バージョン(1.1.0)がレジストリに届いたのは5 か月前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。URLでつながるので、リモートMCPサーバーに対応したアプリ(開発者モードのChatGPTなど)でも使えます。
同じカテゴリには:Spec Driven Development, Remote Desktop Commander, LexPact UK Contracts
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
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作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
A purpose-built analytical engine for financial research, exposed over MCP. Ask hard questions about US-listed equities in plain English and get structured, reproducible results back.
mrmarket.ai is a remote MCP server. Connect it to Claude, ChatGPT, or Gemini and your assistant gains a dedicated engine for resolving financial questions against clean, structured market data. It is not a language model with a database bolted on, and it is not an API wrapper. You describe the analysis; the engine computes it and returns rows, columns, and the assumptions it applied.
The interesting questions in equity research require joins that no single API endpoint will run for you. "Stocks where insiders bought over $1M, free cash flow grew four quarters running, and the price sits below the 200-day moving average" spans insider filings, quarterly cash flow statements, and daily prices at once. mrmarket.ai is built for exactly that class of question.
mrmarket.ai is a remote MCP server reachable at:
https://mcp.mrmarket.ai/mcp
Each connection is tied to a free account so that credit balance and rate limits apply correctly. Authorization happens over OAuth on first use. Create an account and manage connections at mrmarket.ai/connect.
claude mcp add --transport http mrmarket https://mcp.mrmarket.ai/mcp
Open Settings, go to Connectors, choose Add custom connector, and paste the endpoint:
https://mcp.mrmarket.ai/mcp
Claude prompts for authorization on first use. Note that editing claude_desktop_config.json by hand does not work for this server; that file only accepts local, command-based servers, and mrmarket.ai is remote.
In Settings, open Connectors, choose Add custom connector, and point it at the same endpoint.
Add it as a remote MCP extension when prompted by Gemini's MCP onboarding, using the same endpoint.
| Tool | Cost | Purpose |
|---|---|---|
query_data | metered | The workhorse. A natural-language financial question in; structured rows and columns out. Screens, rankings, comparisons, time-series, cohort studies, and event studies are all single calls. |
fetch_page | free | The continuation. When a query_data result is too large for one response, page 1 comes back with a pagination.next_cursor; pass that cursor to fetch_page to retrieve the rest. It runs no new query, so it never costs credits — the original query_data is charged once. |
describe_data | free | The data catalog. Browse categories and fields, or search for a specific metric, before composing a question. |
get_symbols | free | Fast ticker, sector, and industry resolution. Name to ticker, sector membership, or the full universe in under 50ms. |
getting_started | free | A structured orientation tour with verified example prompts, grouped by use case. |
recent_queries | free | Your recent queries, for context and re-runs. |
get_account_status | free | Connected account, plan tier, credit balance, and rate limits. A useful first call in any new session. |
report_issue | free | Flag a result that looks wrong or a feature that is missing. Pass the query_id from the response so the trace can be investigated. |
Seven of the eight tools cost zero credits. Only query_data consumes credits, priced by query complexity. Start with getting_started or describe_data, then move to query_data.
Every prompt below resolves in a single query_data call. Phrase questions the way an analyst would speak them, not as a list of column filters.
Technology stocks with ROIC above 20%, debt-to-equity below 0.5, and 5-year revenue CAGR above 10%.
Healthcare companies with positive free cash flow and gross margin above 50%. Companies with four consecutive quarters of growing free cash flow.
Top 20 stocks by ROIC, excluding financials.
Top 15 companies by smoothness of year-over-year revenue growth over the last five fiscal years. Bottom 10 consumer discretionary stocks by 1-year total return.
Compare AAPL, MSFT, and GOOGL on revenue and net income over the last five years.
AMZN versus WMT operating margin trend over the last decade. NVDA quarterly EPS surprise history.
Stocks whose ROIC is at least one standard deviation above their sector average.
Companies with a net profit margin more than twice their sector average. Companies with revenue growth in the top quartile of their industry.
AAPL daily closes for the last five years with earnings dates overlaid.
MSFT price with insider buy and sell markers over the past two years. 50-day and 200-day moving averages for TSLA.
Average 30-day return after companies beat earnings by more than 10 percent.
Forward 3-month returns following insider purchases above $1M, grouped by sector. Across the large-cap universe, the correlation between monthly insider purchase count and the next 3-month return.
Larger studies decompose into several calls that your assistant orchestrates while mrmarket.ai supplies the ground truth at each step:
For every large-cap stock that gapped down 5 percent or more after earnings in the
past two years, what is the 30, 60, and 90-day recovery rate, and is it statistically significant against random 90-day windows?
Backtest this signal: buy stocks with insider purchases above $500K within 30 days before earnings that then beat EPS estimates, hold for 63 trading days, and report CAGR, maximum drawdown, and win rate against buying every post-beat stock.
Build a pre-earnings watchlist: companies reporting in the next two weeks where insiders bought in the last 90 days, the stock trades below its 200-day moving average, and they beat estimates last quarter.
| Universe | 11,000+ US-listed stocks and ETFs (NYSE, NASDAQ, AMEX) |
| History | 20+ years of financials on US equities |
| Response time | Under 10 seconds for typical questions |
Data spans daily adjusted prices, annual and quarterly financial statements (income statement, balance sheet, cash flow), earnings actuals against estimates, insider transactions, and valuation snapshots, alongside computed metrics such as ROIC, free cash flow, debt-to-equity, ROE, margins, returns, and earnings surprise. Sourced with point-in-time accuracy and curated for cross-dataset queries.
mrmarket.ai is a research and analysis layer, not a brokerage and not a real-time feed. Prices are end-of-day. The following are out of scope: intraday and tick data, options chains, news and transcript text, raw filing text, macro series, FX, crypto, bonds, and futures. When a question reaches an edge, the engine reports it rather than guessing.
Every query_data response carries a stable error_code, plus warnings and assumptions arrays that explain how the question was interpreted. Read those first; they usually point at the cause.
| Symptom | What it means | What to do |
|---|---|---|
QUERY_NOT_UNDERSTOOD | The question was ambiguous or referenced an unsupported metric. | Rephrase with specifics (period type, time range, ranking criterion). Use describe_data to confirm a field exists. |
RATE_LIMITED | You hit your tier's per-minute or per-day cap. | Wait briefly, or check get_account_status for your exact limits. |
INSUFFICIENT_CREDITS | Your credit balance is exhausted. | Top up or upgrade at mrmarket.ai. Not a fault, no retry needed. |
SCHEMA_DRIFT | A data field is temporarily unavailable (mid-update). | Rephrase without the affected scope and try again. |
INVALID_CURSOR / SNAPSHOT_EXPIRED | A fetch_page cursor was malformed or its result snapshot aged out (snapshots live ~15 minutes). | Re-run the original query_data question to get a fresh result and cursor. |
BILLING_UNAVAILABLE / SERVICE_ERROR | A transient server-side issue. | Retry once; the retryable flag will be set. |
| Empty result on a screen | Filters were too tight. | Loosen one threshold (e.g. ROIC > 15% instead of 25%) or widen the time range. |
| A result looks wrong | An assumption or default may not match your intent. | Read the assumptions array. If it still looks wrong, file it with report_issue (include the query_id). |
For a guided tour of capabilities, limits, and worked examples at any time, call the free getting_started tool.
report_issue tool. Pass the query_id from the response so the exact run can be investigated. This is the fastest path because it links directly to the query trace.https://mcp.mrmarket.ai/mcp