Tradememory Protocol vs Yfinance MCP
A side-by-side look at the Tradememory Protocol and Yfinance MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Tradememory Protocol for finance & fintech work as a local process; choose Yfinance MCP for finance & fintech as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Tradememory Protocol when
- You need dedicated capabilities in the Finance & Fintech domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: No auth required.
- You want tools like
get_strategy_performance, get_trade_reflection, remember_trade.
Choose Yfinance MCP when
- You need dedicated capabilities in the Finance & Fintech domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: No auth required.
- You want tools like
yfinance_get_ticker_info, yfinance_get_analyst_price_targets, yfinance_get_analyst_estimates.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Finance & Fintech | Finance & Fintech |
| Quality signal | 68/100 · Great | 64/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | No auth required | No auth required |
| Pricing | Free | Free |
| Required env vars | None listed | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 1,431 | 203 |
| Directory activity | 5 views 0 installs 0 upvotes | 2 views 0 installs 0 upvotes |
| Tools | 20 | 15 |
| Full listing | View Tradememory Protocol | View Yfinance MCP |
Tools & capabilities
Tradememory Protocol tools 20
get_strategy_performanceGet aggregate performance stats per strategy. Use this to evaluate which strategies are working and which need adjustment.get_trade_reflectionGet the full context and reflection for a specific trade. Use this to deep-dive into a particular trade's reasoning and lessons.remember_tradeStore a trade into OWM multi-layer memory with automatic updates. Writes to episodic memory and automatically updates semantic (Bayesian), procedural (running averages + hold time + Kelly), and affective (EWMA confidence/streaks). Also writes to trade_records for backward compatibility.recall_memoriesRecall memories using OWM outcome-weighted scoring. Queries episodic and semantic memories, scores them by outcome quality, context similarity, recency, confidence, and affective modulation. Returns ranked memories with score breakdown.get_behavioral_analysisGet behavioral analysis from procedural memory. Returns aggregate trading behavior stats: hold times, disposition ratio, lot sizing variance, and Kelly criterion comparison.get_agent_stateGet the current agent affective state (confidence, risk, drawdown). Returns confidence level, risk appetite, drawdown percentage, win/loss streaks, equity tracking, and a recommended action based on current drawdown severity.create_trading_planCreate a prospective trading plan that activates when conditions are met. Stores a rule-based plan in prospective memory. The plan stays active until triggered, expired, or manually cancelled.check_active_plansCheck active trading plans against current market context. Queries all active prospective plans, expires any past their expiry date, and matches remaining plans against the provided context.evolution_fetch_market_dataFetch OHLCV market data from Binance for evolution analysis. Downloads historical price bars for backtesting and pattern discovery. Use this before discover_patterns or run_backtest to get data.evolution_discover_patternsDiscover trading patterns from market data using LLM analysis. Uses Claude to analyze OHLCV data and generate candidate trading patterns with entry/exit conditions. Each pattern can be backtested afterward.evolution_run_backtestBacktest a candidate pattern against historical OHLCV data. Takes a pattern dict (from discover_patterns) and runs a vectorized backtest. Returns fitness metrics: Sharpe ratio, win rate, trade count, max drawdown, total PnL.evolution_evolve_strategyRun full evolution loop — generate, backtest, select, eliminate. Multi-generation strategy evolution: generates candidate patterns via LLM, backtests on in-sample data, validates survivors on out-of-sample data, eliminates weak hypotheses. Returns graduated strategies and graveyard.- +8 more on the listing page
Yfinance MCP tools 15
yfinance_get_ticker_infoRetrieve comprehensive stock data including company information, financials, trading metrics and governance. Returns JSON object with fields including: - Company: symbol, longName, sector, industry, longBusinessSummary, website, city, country - Price: currentPrice, previousClose, open, dayHigh, dayLow, fiftyTwoWeekHigh, fiftyTwoWeekLow - Valuation: marketCap, enterpriseValue, trailingPE, forwardPE, priceToBook, pegRatio - Trading: volume, averageVolume, averageVolume10days, bid, ask, bidSize, askSize - Dividends: dividendRate, dividendYield, exDividendDate, payoutRatio - Financials: totalRevenue, revenueGrowth, earningsGrowth, profitMargins, operatingMargins - Performance: beta, fiftyDayAverage, twoHundredDayAverage, trailingEps, forwardEps Note: Available fields vary by security type. Timestamps are converted to readable dates.yfinance_get_analyst_price_targetsFetch the current price and analyst consensus price targets for a stock. Returns a JSON object with the fields supplied by Yahoo Finance: - current: Current market price - low: Lowest analyst price target - high: Highest analyst price target - mean: Mean analyst price target - median: Median analyst price target Analyst coverage and available fields vary by symbol.yfinance_get_analyst_estimatesFetch consensus estimates, EPS/revenue trends, revisions, recommendations, and earnings history.yfinance_get_fund_dataFetch ETF or mutual-fund composition, holdings, exposures, ratings, and operating details.yfinance_get_upgrades_downgradesFetch analyst upgrades, downgrades, initiations, and price target changes. Returns analyst actions newest first. Fields supplied by Yahoo Finance can include: - GradeDate: Date and time of the analyst action - Firm: Analyst firm name - ToGrade and FromGrade: New and previous ratings - Action: Rating action, such as upgrade, downgrade, initiation, or reiteration - priceTargetAction: Price target action, such as Raises, Lowers, or Maintains - currentPriceTarget and priorPriceTarget: New and previous price targets Available fields vary by symbol and analyst action.yfinance_get_ticker_newsFetch recent news articles and press releases for a specific stock. Returns JSON array where each news item has: - id: Unique article identifier - content: Object containing: - title: Article headline - summary: Brief article summary - pubDate: Publication date (ISO 8601 format) - provider: Object with displayName (e.g., "Yahoo Finance") and url - canonicalUrl: Object with article url, site, region, lang - thumbnail: Object with image URLs and resolutions - contentType: Type of content (e.g., "STORY", "VIDEO") Use this to track company announcements, market sentiment, and breaking news.yfinance_searchSearch Yahoo Finance for stocks, ETFs, and news articles. Returns JSON with search results based on search_type: - 'quotes': Array of securities with: - symbol: Ticker symbol - shortname/longname: Company name - quoteType: Security type (EQUITY, ETF, MUTUALFUND, etc.) - exchange: Exchange code - sector: Business sector - industry: Industry classification - score: Search relevance score - 'news': Array of articles with: - uuid: Article identifier - title: Headline - publisher: News source - link: Article URL - providerPublishTime: Unix timestamp - relatedTickers: Array of related symbols - thumbnail: Image URLs - 'all': Object with both 'quotes' and 'news' arrays Use this to find ticker symbols, discover related securities, or search financial news.yfinance_screenRun a Yahoo Finance screener query. Supports predefined Yahoo screener keys and custom equity, mutual-fund, or ETF query trees.yfinance_screen_gappersRun a custom equity screener tuned for opening-session stock gappers.yfinance_get_topGet top-ranked financial entities within a sector. This unified tool provides access to various rankings: - ETFs and mutual funds focused on the sector - Largest companies by market capitalization - Fastest-growing companies by revenue/earnings - Best-performing stocks by price appreciation Returns JSON data with relevant metrics for each entity type.yfinance_get_price_historyFetch historical price data and optionally generate technical analysis charts. When chart_type is None, returns Markdown table with columns: - Date: Trading date (index) - Open: Opening price - High: Highest price - Low: Lowest price - Close: Closing price - Volume: Trading volume - Dividends: Dividend payments (if any) - Stock Splits: Split events (if any) When chart_type is specified, returns a chart image: - 'price_volume': Candlestick chart with volume bars - 'vwap': Price with Volume Weighted Average Price overlay - 'volume_profile': Volume distribution by price level Set prepost=True to include pre-market and post-market data when available. Note: Not all period/interval combinations are valid. Minute intervals (1m, 5m, etc.) only work with short periods (1d, 5d).yfinance_get_financialsFetch financial statements (income statement, balance sheet, and cash flow) with historical data. Returns JSON with income statement, balance sheet, and cash flow data across reporting periods. Use the data to analyze trends, calculate ratios, or compare periods.- +3 more on the listing page
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Tradememory Protocol
{
"mcpServers": {
"mnemox-ai-tradememory-protocol": {
"command": "uvx",
"args": [
"tradememory-protocol"
]
}
}
}
Yfinance MCP
{
"mcpServers": {
"narumiruna-yfinance-mcp": {
"command": "uvx",
"args": [
"yfmcp@latest"
]
}
}
}
Frequently asked questions
Tradememory Protocol is categorized under Finance & Fintech and uses a local stdio subprocess. Yfinance MCP belongs to Finance & Fintech and uses a local stdio subprocess. Pick Tradememory Protocol for finance & fintech work and Yfinance MCP for finance & fintech.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Tradememory Protocol is listed as free. Auth: no auth required. Yfinance MCP is listed as free. Auth: no auth required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add mnemox-ai-tradememory-protocol and narumiruna-yfinance-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Tradememory Protocol has a quality signal of 68/100 (Great) with 5 views, 0 installs and 1,431 GitHub stars. Yfinance MCP has 64/100 (Good) with 2 views, 0 installs and 203 GitHub stars.