Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Self-hosted MCP server: technical indicators + smart-money-concepts from OHLC bars.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"wickworks": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"docker.io/psyb0t/wickworks:v0.7.0"
]
}
}
}Run this in your terminal
claude mcp add wickworks -- docker run -i --rm docker.io/psyb0t/wickworks:v0.7.0Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"wickworks": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"docker.io/psyb0t/wickworks:v0.7.0"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"wickworks": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"docker.io/psyb0t/wickworks:v0.7.0"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
The registry name was verified with the GitHub account psyb0t, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.7.0) reached the registry 2 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, Fomu MCP
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
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.
Kenya government form guides: checklists, draft letters, eCitizen, Huduma, timelines. Sample data.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
The dumb-as-rocks OHLC analyzer. You throw bars at it over HTTP, it throws indicators and SMC objects back. That's the whole product. No database, no queue, no state, no opinions, no "AI-powered signals," no upsell to a $97/mo Discord. Just primitives.
Every snake-oil-flavored TA SaaS out there wants to tell you when to buy. Wickworks tells you the order block is at 1.0832 and the RSI is 71.4. The "what does that mean?" part is where your strategy lives — and it should live in your code, not behind someone else's paywall.
Built on pandas_ta and smartmoneyconcepts, wrapped in a FastAPI server, locked behind 370 tests that diff our output against closed-form references on real EURUSD ticks. If a math bug slips in, the test suite screams before the container builds.
GET /healthGET /metadataPOST / — computeindicators object| Category | Primitives |
|---|---|
| Trend | SMA/EMA + 15 other moving averages, slope, Donchian channels, Ichimoku |
| Momentum | RSI, MACD, Stochastic, StochRSI, ADX, MFI, CCI, Williams %R, ROC, MOM, TSI, TRIX, UO, Fisher |
| Volatility | ATR, NATR, Bollinger Bands, Keltner Channels, Squeeze |
| Volume | VWAP (anchored), VWMA, OBV, AD, ADOSC, CMF, KVO |
| SMC | Order Blocks, Fair Value Gaps, BOS/CHoCH, swing structure, S/R levels, liquidity, retracements, sessions, previous-period H/L |
| Summaries | Position, slope, momentum, volume regime, recent range — pre-baked projections over the raw series |
All JSON field names are camelCase. Output is NaN-safe — NaN becomes null, never a literal NaN token that blows up downstream parsers. NumPy/Pandas scalars and arrays are serialized cleanly (no numpy.float64(...) leaks). Bars in UTC, math in UTC, container runs TZ=UTC — timezone bullshit is your problem, not ours.
docker run --rm -p 8000:8000 psyb0t/wickworks:latest
That's it. The service listens on :8000.
services:
wickworks: image: psyb0t/wickworks:latest ports: ["8000:8000"] environment: LOG_LEVEL: INFO MAX_BARS: "5000" MIN_BARS: "50"
make run # build the dev image and run uvicorn on :8000
Three endpoints. That's the whole surface.
GET /healthcurl -s http://localhost:8000/health
{ "ok": true, "version": "0.7.1" }
GET /metadataReturns the versioned catalog of labels, descriptions, units, categories, and interpretation notes for every output path. Consumers can cache it for the reported Wickworks version.
POST / — computeSend OHLC(V) bars + the indicators you want. Get back only what you asked for — response keys mirror the keys you sent. No "let me also throw in 40 indicators you didn't ask for" energy.
curl -s -X POST http://localhost:8000/ \
-H 'Content-Type: application/json' \ -d '{ "symbol": "EURUSD", "timeframe": "H1", "bars": [ { "time": 1700000000, "open": 1.0832, "high": 1.0851, "low": 1.0828, "close": 1.0844, "volume": 1247 }, ... ], "indicators": { "rsi": true, "rsi21": { "type": "rsi", "length": 21 }, "stochFast": { "type": "stoch", "k": 5, "d": 3, "smoothK": 3 }, "stochSlow": { "type": "stoch", "k": 21, "d": 7, "smoothK": 5 }, "macd": true, "orderBlocks": true, "fvg": true } }'
indicators object — the whole pointEach entry maps an output name (the key) to a spec:
true — run the indicator with default params; key doubles as the type.{ ...params } — params object; missing type falls back to the key.{ "type": " ", ...params } — run a known indicator under a custom output name. This is how you stack multiple instances of the same indicator (e.g. four stochs with different params, three EMAs at different lengths)."indicators": {
"rsi": true, "rsi21": { "type": "rsi", "length": 21 }, "stochA": { "type": "stoch", "k": 5, "d": 3 }, "stochB": { "type": "stoch", "k": 21, "d": 7 } }
The response contains rsi, rsi21, stochA, stochB. Nothing else. Duplicate output names are physically impossible by JSON-object construction — you can't shoot yourself in the foot with this API even if you try.
The outputs below map to a handful of recurring trading ideas. If you've used any TradingView-style charting tool most of these will be familiar; if not, the short framing here is enough to pick the right output for the job.
Series vs events. A _Series_ output is one value per input bar (warmup positions are null) — these are continuous quantities you can chart. An _event_ output is a sparse array of objects pinpointing things that just happened (a swing, a block, a structure break). Series tell you _state_; events tell you _occurrences_.
Primitives only — no signals. Wickworks does not emit interpretive signals (no divergence detection, no MA-cross events, no "buy/sell" tags). Everything returned is either a raw indicator series, a structural fact (an order block was formed at this bar, price closed past this swing), or a pre-baked summary over those — never a judgment about what to do. If you want divergences, MACD-cross events, golden/death crosses, or any other derived signal, build that layer in your own consumer.
The four questions every indicator answers part of:
In-house event constructs you won't find on TradingView:
Want the formal contract for tooling / validators? See
schema.json— full JSON Schema Draft 2020-12. The reference below is the human version: categories + per-indicator blurbs + params tables + return shapes + examples.
Three series shapes are shared across most outputs:
number | null), aligned 1:1 with input bars. Warmup positions are null.0/1 integer per bar.-1/+1 integer per bar (1 = bullish/long, -1 = bearish/short).Indicators below are grouped by what they tell a trader, not by parameter shape. Each subsection starts with a one-paragraph framing of the category, then lists every indicator in it with a short "what it is / when to use it" blurb.
Smoothed price lines. Each flavor trades responsiveness against lag differently — pick by how fast you want the curve to react to new bars. Trader use: define the dominant direction (price above/below the MA = bull/bear bias), identify dynamic support/resistance the market keeps touching, fire crossover signals (fast MA crossing slow MA = trend shift).
All take a single length parameter and return a Series.
type | default | inputs | what it is |
|---|---|---|---|
ema | 21 | close | Exponential MA — recent bars weighted more. Standard trend filter. The default trend MA in most strategies. |
sma | 50 | close | Simple MA — flat average. Slow, smooth, classic. 50/200-SMA crosses define the "Golden Cross" / "Death Cross". |
hma | 14 | close | Hull MA — low-lag, smooth. Reacts fast without the noise an EMA would give at the same period. |
wma | 14 | close | Weighted MA — linear weights. Sits between SMA and EMA in lag. |
dema | 10 | close | Double-EMA — less lag than EMA via a correction term. |
tema | 10 | close | Triple-EMA — even less lag, but more whipsaw-prone in chop. |
t3 | 10 | close | Tillson T3 — smooth like SMA, fast like EMA. Curve-looking output some traders prefer for visual clarity. |
kama | 10 | close | Kaufman Adaptive MA — speeds up in trends, slows down in chop. Self-tuning. |
alma | 10 | close | Arnaud Legoux MA — Gaussian-weighted. Low noise, low lag tradeoff. |
linreg | 14 | close | Linear-regression MA — best-fit line over the window, evaluated at "now". Statistically grounded smoothing. |
jma | 7 | close | Jurik MA — proprietary smooth, very low lag. Premium-feeling curve. |
zlma | 10 | close | Zero-Lag MA — error-correction on EMA, attempting to remove lag entirely. |
rma | 10 | close | Wilder's smoothing — used inside RSI/ATR. Heavy, slow. Useful when you want indicator-internal smoothing semantics. |
| fwma | 10 | close | Fibonacci-weighted MA — weights by Fib sequence.
Only the beginning is shown; read the rest in the repo