| name | FMP Technical Analysis |
| description | [FREEMIUM โ free tier with API key] Use the fmp-mcp-server technical indicator tools for quantitative technical analysis. Invoke when calculating moving averages (SMA, EMA, WMA, DEMA, TEMA), momentum indicators (RSI, Williams %R, ADX), or volatility measures (standard deviation). Supports multiple timeframes from 1-minute to monthly for both intraday and swing trading analysis. |
FMP Technical Analysis Skill
Overview
This skill covers the 9 technical indicator tools provided by the fmp-mcp-server MCP integration. These tools query Financial Modeling Prep (FMP) for real-time and historical technical indicator data, enabling quantitative analysis across multiple timeframes.
Available Tools
Moving Averages
fmp_sma โ Simple Moving Average
- Purpose: Trend direction identification, dynamic support/resistance levels.
- Key Inputs:
symbol, periodLength, timeframe
- How it works: Calculates the unweighted arithmetic mean of closing prices over the specified period. Equal weight is given to every data point in the window.
- Typical periods: 20 (short-term), 50 (medium-term), 200 (long-term).
fmp_ema โ Exponential Moving Average
- Purpose: Trend detection with heavier weighting on recent prices, making it more responsive than SMA.
- Key Inputs:
symbol, periodLength, timeframe
- How it works: Applies an exponential decay weighting so that the most recent prices contribute more to the average.
- Typical periods: 9, 12, 20, 26, 50.
fmp_wma โ Weighted Moving Average
- Purpose: Linear-weighted trend following that prioritizes recent data.
- Key Inputs:
symbol, periodLength, timeframe
- How it works: Assigns linearly increasing weights to each data point in the window (the most recent price gets the highest weight).
- Typical periods: 10, 20, 50.
fmp_dema โ Double Exponential Moving Average
- Purpose: Reduced-lag trend following for faster signal generation.
- Key Inputs:
symbol, periodLength, timeframe
- How it works: Combines a single EMA with an EMA-of-EMA to cancel out a portion of the inherent lag.
- Typical periods: 12, 20, 50.
fmp_tema โ Triple Exponential Moving Average
- Purpose: Minimal-lag trend following for the most responsive moving average signals.
- Key Inputs:
symbol, periodLength, timeframe
- How it works: Extends the DEMA concept with a third layer of exponential smoothing, further reducing lag.
- Typical periods: 12, 20, 50.
Momentum Indicators
fmp_rsi โ Relative Strength Index
- Purpose: Identify overbought and oversold conditions.
- Key Inputs:
symbol, periodLength, timeframe
- Interpretation: Values above 70 suggest overbought conditions; values below 30 suggest oversold conditions. The 50 level acts as a bullish/bearish divider.
- Typical period: 14.
fmp_williams โ Williams %R
- Purpose: Momentum oscillator measuring the current close relative to the high-low range over a lookback period.
- Key Inputs:
symbol, periodLength, timeframe
- Interpretation: Readings above -20 indicate overbought; readings below -80 indicate oversold. The scale runs from 0 to -100.
- Typical period: 14.
fmp_adx โ Average Directional Index
- Purpose: Measure trend strength regardless of direction.
- Key Inputs:
symbol, periodLength, timeframe
- Interpretation: Values above 25 indicate a strong trend; values below 20 suggest a weak or range-bound market. ADX does not indicate direction, only strength.
- Typical period: 14.
Volatility
fmp_stddev โ Standard Deviation
- Purpose: Quantify price volatility over a given period.
- Key Inputs:
symbol, periodLength, timeframe
- How it works: Calculates the statistical standard deviation of closing prices, providing a measure of dispersion around the mean.
- Typical periods: 20, 30.
Supported Timeframes
All 9 tools accept the same set of timeframe values:
| Value | Description |
|---|
1min | 1-minute bars |
5min | 5-minute bars |
15min | 15-minute bars |
30min | 30-minute bars |
1hour | 1-hour bars |
4hour | 4-hour bars |
1day | Daily bars |
1week | Weekly bars |
1month | Monthly bars |
Use shorter timeframes (1min through 1hour) for intraday and day-trading analysis. Use longer timeframes (1day through 1month) for swing trading and position analysis.
Usage Patterns
1. Trend Analysis โ Golden/Death Cross Detection
Combine a short-period SMA with a long-period SMA to detect major trend reversals.
fmp_sma(symbol="AAPL", periodLength=50, timeframe="1day")
fmp_sma(symbol="AAPL", periodLength=200, timeframe="1day")
- Golden Cross: The 50-day SMA crosses above the 200-day SMA โ bullish signal.
- Death Cross: The 50-day SMA crosses below the 200-day SMA โ bearish signal.
Compare the most recent values from both responses. If sma_50 > sma_200 and the previous period had sma_50 < sma_200, a golden cross has just occurred.
2. Mean Reversion โ RSI + Standard Deviation
Use RSI to identify overbought/oversold extremes and standard deviation to add volatility context.
fmp_rsi(symbol="MSFT", periodLength=14, timeframe="1day")
fmp_stddev(symbol="MSFT", periodLength=20, timeframe="1day")
- High-confidence oversold: RSI < 30 AND stddev is elevated (price has deviated significantly from mean โ reversion is likely).
- High-confidence overbought: RSI > 70 AND stddev is elevated.
- If stddev is low while RSI is extreme, the move may lack the volatility to snap back quickly.
3. Momentum Screening โ ADX + EMA Filter
Filter for stocks in strong trends, then confirm direction with EMA.
fmp_adx(symbol="NVDA", periodLength=14, timeframe="1day")
fmp_ema(symbol="NVDA", periodLength=20, timeframe="1day")
- Strong uptrend: ADX > 25 AND current price is above the 20-period EMA.
- Strong downtrend: ADX > 25 AND current price is below the 20-period EMA.
- Avoid: ADX < 20 indicates a weak or non-trending market โ momentum strategies are less reliable.
4. Multi-Timeframe Confirmation
Run the same indicator across multiple timeframes to confirm signals and avoid false entries.
fmp_rsi(symbol="TSLA", periodLength=14, timeframe="1day")
fmp_rsi(symbol="TSLA", periodLength=14, timeframe="1hour")
fmp_rsi(symbol="TSLA", periodLength=14, timeframe="15min")
- Strong signal: All three timeframes agree (e.g., all show oversold below 30).
- Weak signal: Only the shortest timeframe shows the condition โ likely noise.
- General rule: Higher timeframes carry more weight. A daily oversold reading confirmed by hourly and 15-min is a higher-conviction setup than a 15-min reading alone.
Best Practices
- Always specify
periodLength and timeframe explicitly. Do not rely on defaults; being explicit ensures reproducible analysis.
- Combine indicators from different categories. A moving average (trend) paired with RSI (momentum) and stddev (volatility) gives a more complete picture than any single indicator alone.
- Use multi-timeframe analysis for entry timing. Identify the trend on a higher timeframe, then time entries on a lower timeframe.
- Watch for divergences. When price makes a new high but RSI or Williams %R does not, a reversal may be forming.
- ADX is non-directional. A rising ADX means the trend is strengthening, but you must use price action or a moving average to determine whether the trend is up or down.
- Prefer EMA/DEMA/TEMA over SMA when reduced lag is important โ for example, in fast-moving intraday markets. Use SMA for widely followed levels like the 200-day moving average, where institutional alignment matters.
