Describe a trading strategy in plain English and deploy a live signal model in one call. No signup.
| Endpoint | https://mcp.quantifyme.ai/mcp (streamable-http) |
|---|---|
| Registry version | 1.0.0 |
| Now | 13 tools · grade C (77) · pin ts_ab2a2e46b9119ffd5d35a3209812ff12 · protocol 2025-06-18 |
| First / last listed | 2026-10-27 08:37 UTC / 2026-10-27 08:37 UTC |
| Grade over time | 2026-10-27: C (77), 13 tools |
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Tools: one_shot get_deploy_result link_account list_models list_deployed top_up generate_strategy browse_community find_strategy get_strategy_code get_quote get_model_chart stream_test
one_shot | End-to-end deploy: generate strategy → train → deploy live.
One of `prompt` (free-form NL), `preset` (curated winning strategy), or
`community_id` (copy a published community strategy) is required. If more
than one is passed, precedence is community_id > preset > prompt.
Args:
prompt: Natural-language strategy description (e.g. "Buy when RSI < 30, sell > 70").
symbol: params: prompt, symbol, timeframe, claude_model, preset, community_id, webhook_url, telegram_chat_id |
get_deploy_result | Wait for a `one_shot` deploy to finish and return its final result.
`one_shot` returns a job_token immediately and the LIVE CARD already streams
progress and renders the interactive backtest chart itself. Call this ONCE with
the token to get the final numbers as TEXT so you can summarize them — it does
NOT render another card (no need for get_model_chart). It BLOCKS until the depl params: job_token* |
link_account | Link this chat to the user's existing QuantifyMe account.
Call this when the user says they already have a QuantifyMe account, or
asks why their models are missing / where a model went, or wants what they
deploy here to show up in their own dashboard.
By default this connector works with NO signup: it mints an anonymous trial
account per MCP session, so models deployed here b params: none |
list_models | List the user's trained models with pre-computed train/test stats.
`acting_as` names the identity listed: the linked account or a trial user (#1962). params: none |
list_deployed | List the user's currently deployed (live) models. params: none |
top_up | Simulated crypto top-up for a QuantifyMe DEV server only: no money moves,
so it never makes an account paid and grants at most up to the free credit
cap ($100 per call). quantifyme.ai refuses it (#1098) and answers with how to
pay for real: send USDC on Base to your deposit address
(GET /api/v1/wallet/deposit_address). Returns your new credit balance. params: amount_usd* |
generate_strategy | Generate Python strategy code (no training/deploy). Use when the user wants raw code.
Args:
features: NL description of features (e.g. "RSI 14, Bollinger Bands").
signals: NL description of signal logic (e.g. "Buy when RSI < 30").
model: ML model name (default Random Forest).
risk: NL risk rules (e.g. "0.5% stop loss").
description: Optional one-line summary; tre params: features, signals, model, risk, description, symbol, timeframe, claude_model |
browse_community | Browse the public community leaderboard of published strategies, ranked
by a composite performance score (best first). No signup or key needed.
Copy-trade flow: call this to find a top strategy, then pass its `id` to
`one_shot` as `community_id` to deploy a live signal model running that
exact strategy in one call.
Args:
limit: How many top entries to return (default 20 params: limit, sort |
find_strategy | Find an existing PROVEN strategy that matches a plain-English idea, so you
can offer the user a choice — deploy the existing one, or generate a fresh
custom one. Mirrors the quantifyme.ai landing experience: "Found <X> by
@<author> (WR/PF) — Use it / Generate fresh".
Use this when a user wants to browse for an existing strategy. A vague deploy
request does NOT need it: one_sho params: description*, symbol, timeframe |
get_strategy_code | Get the actual Python code behind a community leaderboard strategy.
Use after `browse_community`: pass an entry's `id` here to read its real
`feature_engineering()` + `strategy_config()` source so the user can
inspect or tweak it. To deploy it unchanged, pass the same id to
`one_shot` as `community_id`. Read-only, no signup needed.
Args:
community_id: The `id` of a comm params: community_id* |
get_quote | Get the latest price for a G7 FX pair — a quick "what's it at now" check.
Useful for context before deploying a strategy. The price is the close of
the most recent 1-minute bar from the platform's market feed (not a raw
live tick); FX markets close on weekends, so the `stale` flag marks a bar
that is more than 15 minutes old.
Args:
symbol: G7 pair — one of EURUSD, USDJP params: symbol |
get_model_chart | Visualize a trained model's backtest — a cumulative-return chart + trade log + stats.
Use after `one_shot` / `list_models` with the model's `stem` to SHOW the user how it
traded (the "is it actually any good" view). In ChatGPT this renders an interactive
widget. In Claude, render an interactive **artifact** from this tool's structured
output: a line chart of the cumulative return params: stem* |
stream_test | Diagnostic: test whether LIVE data streaming works in this client.
Renders a widget with three panels: a JS timer (baseline), the WebSocket
panel (not offered: the feed needs a credential and none is sent to a
widget), and an HTTP poll of /quote, each showing a live value + status, so
you can see which streaming mechanisms the client's widget sandbox permits.
Use when a live/t params: symbol |
Entries describe changes in tool definitions. They are not statements about a server, its quality or its author. The grade measures how the tool definitions fit model providers (token cost, schema compatibility, confusable names) as scored by the ToolFit engine at the time of the listing. JSON: append .json. Opt-out: how or hello@youraitools.co.