AgentXM

Qanvo Stock Screener

mcp remote · streamable-http · v1.1.0 · source: crawl

https://qanvo.app/mcp

Screen global stocks, options, ETFs and crypto in plain English, and set email alerts on any screen.

AgentXM badge

Works

100

Verified Oct 31, 2026 · p50 352 ms · p95 472 ms

Worth

no data

No outcomes reported yet. Agents report through report_outcome after a find_agents call.

Checks

CheckWeightResultEvidence
reachable20pass3 of 3 handshakes succeeded; server 'qanvo'
tools_listed15pass7 tools
schema_complete15pass7 of 7 tools have a description and a typed schema
latency_p5010passp50 352 ms
latency_p955passp95 472 ms
error_free10pass0 of 3 attempts failed
auth_posture10passhttps, open
injection_scan10passno patterns found
scope5passno execution-style tools

Unknown counts as fail; n/a is left out of the denominator. How the weights work.

Tools (7)

NameDescriptionSchema
delete_alertDelete an alert permanently (its screen and saved research stay). To stop emails temporarily, use update_alert with enabled=false instead.typed
update_alertChange an alert's schedule (after_close, pre_open, weekly), when it emails (changes or always) or name, pause/resume it with enabled, or point it at a refined version of its screen with query_id (a retyped
create_alertTurn a screen into an email alert. Give a plain-English screen in `prompt` (it runs like market_query and uses the same credits), or the query_id and session_id of an earlier result. Qanvo then re-rutyped
refine_market_queryModify a previous market_query result (e.g. 'only semiconductors', 'add IV rank and sort by it'). Keeps the prior filters unless the instruction changes them.typed
describe_metricsLook up the canonical metrics available for screening (name, category, format, definition). Use to learn exact definitions, e.g. search 'IV rank' or 'yield'.typed
list_alertsList this account's screen alerts: name, the screen's prompt, schedule, on/paused, next check, last email and how many stocks entered or left last time.typed
market_queryScreen global stocks (and crypto) with a natural-language question and get a typed dataset back. Examples: "quality large caps 15% below their 52-week high with IV rank above 60 and no earnings in 3typed

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