Alpaca Trading API integration for Model Context Protocol (MCP)
Nothing to run from here
Quantifyme is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
13
tools declared
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trust score
remote
at its publisher
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calls last 7d
What it does
Describe a trading strategy in plain English and deploy a live signal model in one call. No signup.
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user --transport http quantifyme-mcp https://mcp.quantifyme.ai/mcp
# 2 — ask your agent for something these tools do
# one_shot, get_deploy_result, link_account and 10 more
Quantifyme costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publishernot claimed
MQAll 1 server
mcp.quantifyme.ai1 server
1 category
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Installation
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. Nothing here runs on your machine and nothing runs on ours: this server answers at its publisher’s own address, and what you install is the connection straight to it.
Claude Codedeclared by this listing
This is a public server: it answers at its publisher’s own address and this marketplace is not in the path. Claude Code registers it in one command; --scope user makes it available in every project. The transport below is http, as the publisher's own manifest declares it.
claude mcp add --scope user --transport http quantifyme-mcp https://mcp.quantifyme.ai/mcpReconnect, or start a new session, and the tools appear in the model’s tool list.
Free on mcprush, and it answers at its publisher’s own address: this marketplace is not in the path, so there is no key of ours to hold and no card to add.
What it writes
One config entry pointing straight at the publisher’s own address — this marketplace is not in the path, and nothing from this listing executes on your machine.
What you approve
13 tools, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.
Tool surface
What the model actually sees. Descriptions are diffed on every release — see version history.
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:
| Parameter | Type | Required | Notes |
|---|---|---|---|
| prompt | no | — | |
| symbol | no | — | |
| timeframe | no | — | |
| claude_model | no | — | |
| preset | no | — | |
| community_id | no | — | |
| webhook_url | no | — | |
| telegram_chat_id | no | — |
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
| Parameter | Type | Required | Notes |
|---|---|---|---|
| job_token | string | yes | — |
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
No parameter schema on file.
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).
No parameter schema on file.
List the user's currently deployed (live) models.
No parameter schema on file.
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.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| amount_usd | number | yes | — |
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
| Parameter | Type | Required | Notes |
|---|---|---|---|
| features | string | no | — |
| signals | string | no | — |
| model | string | no | — |
| risk | string | no | — |
| description | no | — | |
| symbol | no | — | |
| timeframe | no | — | |
| claude_model | no | — |
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
| Parameter | Type | Required | Notes |
|---|---|---|---|
| limit | integer | no | — |
| sort | string | no | — |
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
| Parameter | Type | Required | Notes |
|---|---|---|---|
| description | string | yes | — |
| symbol | no | — | |
| timeframe | no | — |
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
| Parameter | Type | Required | Notes |
|---|---|---|---|
| community_id | integer | yes | — |
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
| Parameter | Type | Required | Notes |
|---|---|---|---|
| symbol | string | no | — |
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
| Parameter | Type | Required | Notes |
|---|---|---|---|
| stem | string | yes | — |
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
| Parameter | Type | Required | Notes |
|---|---|---|---|
| symbol | string | no | — |
Free
$0 forever
- Every tool — any call limit is its publisher’s, not ours
- No card, and mcprush charges nothing for it
- Runs at its publisher’s own address — this marketplace is not in the path
- Nothing to cap, because mcprush bills nothing
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable: mcprush charges nothing to install Quantifyme or to call it, at any volume.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
—
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Alert at 80% · then the tool returns a normal MCP error
Used this month: —
—Grade not published
No rule-by-rule report on file for this release
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
This listing is an address its publisher runs, and you connect to it directly — this marketplace is not in the path. The scanner reads packages and public source, and an address is neither. So there is no grade — not a withheld one, an unmeasured one.
Release history
This is an address its publisher runs: which release it serves is theirs to choose, so there is nothing here to pin. The history below is for reading; the current release on file is 1.0.0.
1.0.0
undated
latestNo release note was published with this version.
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no reviews yet
Who can review
One review per account, from a signed-in account that does not publish this listing. Nothing else is asked — you can say what you think before you install it. Publishers can reply once per review, and a review can be edited or deleted by whoever wrote it.
Sign in to write one
Any signed-in account that does not publish Quantifyme can review it, once — before installing it or after. A review from an account that has installed it is marked as one.
No reviews yet
Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes a signed-in account that does not publish it, and nothing else.