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Vecviz

↗ vecviz.com official website

**Interrogate a quantitative equity model -- do not just read its output.** VecViz publishes daily model output for > 700 US tickers: VNA target prices, proba…

infrastructurePricing checked daily
Agentery value verdictPriced near the marketfrom $39/mo
Observed entry price$39/molowest observed monthly
Billing modelunclear
Pricing observed17 Oct 2026latest priced read of the page
Website liveness18 Oct 2026alive · separate from pricing

What it does

The specific capability behind this listing, and where to get it.

**Interrogate a quantitative equity model -- do not just read its output.** VecViz publishes daily model output for > 700 US tickers: VNA target prices, probability-weighted price bands, a six-horizon V-Score, VecEvents, channel geometry, correlation, risk history, model portfolios and option fair value estimates. **Start with `vecviz_read`** -- one ticker, self-sufficient: target, channels, VecEvents, V-Score and which price-probability bands exist. `vecviz_catalog` (free) lists what is covered. ### What makes it different Most finance MCP servers wrap quotes and fundamentals. This one exposes the model itself, so an agent can audit a number instead of quoting it: * **Why a target is what it is** -- `vecevent_matrix` returns each VecEvent's contribution to the VNA target, per Vector Set. * **What it is built on** -- `vector_set_anchors` returns the historical tops and bottoms each channel is drawn over. * **What it becomes if you disagree** -- `vna_scenario` re-prices the target

MCPMCPautonomy: infrastructure

Pricing & plans

Observed public pricing for Vecviz, benchmarked against comparable providers. Plans, tiers, history and scenario below.

Pricing · observed daily
VecViz Full Access · market position

$39 /mo

11.4% above the Pro flat median. Basis: Pro flat plans in Quantitative Analysis Agent, same buyer tier and billing unit, 3 providers, USD monthly, observed 2026-10-17. Thin evidence — fewer than five comparable providers; treat as indicative. Separately, across all Pro-tier plans in the niche regardless of billing unit (6 providers): cheaper than 1 of them.
this agent · $39
$18median $35$70
pricing observed 2026-10-17 · page rechecked daily · source evidence retained
What should this agent charge?

This plan sits close to the comparable median.

pricing recommendation
$39
$18–$70
$35

$39 sits inside the observed Pro flat range ($29.75–$40.25) — around the 56th percentile of observed prices — squarely at market.

Pricing checks returned

Why Agentery reaches that view

price_benchmark

11.4% above the Pro flat median.

get_provider_profile · plan history

VecViz Full Access observed 2026-10-17.

pricing recommendation

~56th percentile of comparable Pro flat plans (approximate: interpolated between the cohort’s observed quartiles, 3 providers).

confidence

thin (thin cohort); source page rechecked daily.

Interactive provider scenario

Test a different price for this plan.

Move the proposed monthly price. Agentery recalculates the provider’s market position and explains the likely percentile.

$39 / month
$18 lowestmedian $35$105 highest
At-market position. At $39/month, this plan is 11.4% above the Pro flat median (3 providers).
—
+11.4%
$18–$70

Is Vecviz good value?

How its price compares with genuinely comparable providers.

Priced near the market

Priced near the market for its buyer tier.

Basis: Pro flat plans at the same billing unit (3 providers), USD monthly, pricing observed 2026-10-17. The VecViz Full Access plan ($39/mo) sits 11.4% above that median of $35. Thin evidence: fewer than five comparable providers, so treat the position as indicative. Other cohorts on this page (niche-wide tier peers, nearest products by capability) are labelled where they appear.

Observed commercial price$39/mo
NicheQuantitative Analysis Agent
Price benchmarkapplicable
How it compares

Compared with Quantitative Analysis Agent

Positioned against the observed p25 / median / p75 of comparable providers at the same buyer tier and billing unit (the basis is stated with each verdict above). See the plans above for the percentile and its cohort size, and the full niche market for peers.

View the full niche →

Vecviz's local market

Nearest products by what they do — a different cohort from the buyer-tier benchmark above.

See the full market →
See the MCP response behind this page · get_provider_profile()
See the MCP response behind this pageget_provider_profile (get_agent_profile remains a callable alias)
{
  "agent_id": "vecviz",
  "name": "Vecviz",
  "url": "https://vecviz.com",
  "logo": "https://agentery.com/logos/CP-EDK73C-128.png",
  "niche": "quantitative-analysis-agent",
  "category": "financial-services",
  "short_summary": "**Interrogate a quantitative equity model -- do not just read its output.**\n\nVecViz publishes daily model output for > 700 US tickers: VNA target prices, proba…",
  "task_performed": "**Interrogate a quantitative equity model -- do not just read its output.**\n\nVecViz publishes daily model output for > 700 US tickers: VNA target prices, probability-weighted price bands, a six-horizon V-Score, VecEvents, channel geometry, correlation, risk history, model portfolios and option fair value estimates.\n\n**Start with `vecviz_read`** -- one ticker, self-sufficient: target, channels, VecEvents, V-Score and which price-probability bands exist. `vecviz_catalog` (free) lists what is covered.\n\n### What makes it different\n\nMost finance MCP servers wrap quotes and fundamentals. This one exposes the model itself, so an agent can audit a number instead of quoting it:\n\n* **Why a target is what it is** -- `vecevent_matrix` returns each VecEvent's contribution to the VNA target, per Vector Set.\n* **What it is built on** -- `vector_set_anchors` returns the historical tops and bottoms each channel is drawn over.\n* **What it becomes if you disagree** -- `vna_scenario` re-prices the target",
  "inputs_accepted": [],
  "outputs_produced": [],
  "integrations_available": [
    "MCP"
  ],
  "protocols_or_interfaces": [
    "MCP"
  ],
  "industry_fit": [
    "general business"
  ],
  "autonomy_level": "infrastructure",
  "human_approval_needed": "unclear",
  "pricing_model": "unclear",
  "price": {
    "observed": true,
    "billing": "freemium",
    "source_kind": "vendor",
    "currency": "USD",
    "lowest_monthly_usd": null,
    "monthly_usd": null,
    "headline": "Free",
    "commercial": {
      "currency": "USD",
      "lines": [
        {
          "name": "Free demo universe",
          "price": "Free",
          "kind": "free",
          "billed": "monthly"
        }
      ]
    },
    "summary": "Free. VecViz offers a free 10-ticker preview/trial, while full access to 700+ tickers and additional features is available by subscription with no public price shown.",
    "confidence": "medium",
    "source_url": "https://vecviz.com/",
    "checked_at": "2026-10-18T03:12:35.179Z",
    "amount": null,
    "display": null,
    "plans": [
      {
        "name": "Free demo universe",
        "price": "Free",
        "period": null,
        "persona": "free",
        "highlights": [
          "10 tickers",
          "No signup for the preview",
          "Free API-key trial with no email"
        ],
        "promo_note": null,
        "price_promo": null,
        "price_annual": null
      }
    ],
    "source": "render+llm"
  },
  "trust_or_rating_signal": [],
  "evidence_quality": "medium",
  "entity_type": "infrastructure",
  "regulated_data_suitability": "unclear",
  "evidence_urls": [
    "https://vecviz.com"
  ],
  "last_checked": "2026-09-02",
  "how_to_connect": {
    "website": "https://vecviz.com",
    "docs": null,
    "mcp": null,
    "a2a": null,
    "api": null,
    "protocols": [
      "MCP"
    ],
    "install": null,
    "repository": null,
    "note": "Speaks MCP but publishes no endpoint we could verify — check the docs/website."
  },
  "deployment": {
    "model": "unknown",
    "both_offered": false,
    "hosted_endpoint": null,
    "install": null,
    "note": "No deployment evidence held — Agentery has no endpoint, install instruction or directory attribute for this listing.",
    "evidence": null
  },
  "licence": {
    "name": null,
    "note": "No named licence found in the retained page text or source attributes. A public repository alone does not establish an open-source licence.",
    "evidence": null
  },
  "evidence_checks": {
    "price": {
      "source_url": "https://vecviz.com/",
      "last_observed_day": "2026-10-18",
      "age_days": 1,
      "verified_day": "2026-10-18",
      "note": "verified = the page-text gate ran for that scan day (day-before/day-of text check)"
    },
    "agent_card": {
      "status": "unknown",
      "note": "no Agent Card URL recorded for this listing"
    },
    "endpoint": {
      "status": "unknown",
      "note": "endpoint not yet checked"
    }
  },
  "product_group": {
    "group_id": 9,
    "group": "Financial research and market data",
    "change_90d_pct": 0,
    "fair_price_by_tier_monthly_usd": {
      "individual": 19,
      "pro": 29,
      "team / small business": 198.5,
      "enterprise": 952.25
    },
    "note": "Change of the group's price index over the last 90 days. Call get_group_fair_price with group_id for tier and payment-model detail.",
    "page": "https://agentery.com/aepi/groups/9"
  },
  "liveness": {
    "probed": true,
    "alive": true,
    "endpoint_kind": "site",
    "latency_ms": 746,
    "uptime_7d": 1,
    "checked_at": "2026-10-18T02:45:49.253Z",
    "consecutive_failures": 0,
    "status": "alive"
  },
  "price_extras": {
    "free_tier": null,
    "unit_cost": null
  },
  "reported_success": null,
  "feedback": "If you actually use this provider, call report_outcome with the result. Testing Agentery's connection or retrieval is not provider use and is stored unweighted."
}