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Graffeo Coffee Roasting

REMOTE · API.AGENTICSHELF.AI · SCANNED AUG 3

Live MCP catalog for Graffeo Coffee Roasting - Simply the World's Finest Coffee since 1935.

+6 this week 65 Trust /100
Trust breakdown (6 categories)

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score →

Endpoint Security63
Transport & Reachability100
Schema Quality & AI Usability66
  • AI-judged instruction clarity (excellent).Pass
  • Context-footprint check failed: tool/resource definitions use about 1643 tokens (~234/item across 7 items; 7 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management27
  • Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage71
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 0% of tool parameters carry a description.Fail
  • Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Capabilities100
  • Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Install

Add this component to your MCP client. Where a client-specific snippet is available, pick your client below and copy it straight into your config; otherwise use the connection detail shown.

remote · api.agenticshelf.ai

# add to Claude Code
claude mcp add --transport http ai-agenticshelf-graffeo https://api.agenticshelf.ai/m/graffeo/mcp
# ~/.codex/config.toml
[mcp_servers.ai-agenticshelf-graffeo]
url = "https://api.agenticshelf.ai/m/graffeo/mcp"
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "ai-agenticshelf-graffeo": {
      "type": "remote",
      "url": "https://api.agenticshelf.ai/m/graffeo/mcp",
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add ai-agenticshelf-graffeo --url https://api.agenticshelf.ai/m/graffeo/mcp --transport streamable-http
# ~/.hermes/config.yaml
mcp_servers:
  ai-agenticshelf-graffeo:
    url: "https://api.agenticshelf.ai/m/graffeo/mcp"
// mcp.json
{
  "mcpServers": {
    "ai-agenticshelf-graffeo": {
      "type": "http",
      "url": "https://api.agenticshelf.ai/m/graffeo/mcp"
    }
  }
}

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 3 Aug 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes.

  • 1 Aug 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 17 to 20. That category is still filling its 30-day observation window: 5 days of observed history at the previous scan, 6 at this one. The score rises as the window fills, whether or not the server changes.

  • 31 Jul 26 +2
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 30 Jul 26 +1
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 29 Jul 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 7 to 10. That category is still filling its 30-day observation window: 2 days of observed history at the previous scan, 3 at this one. The score rises as the window fills, whether or not the server changes.

  • 27 Jul 26 +1
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 26 Jul 26 58

    First indexed and scored.

Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 3 Aug 2026 · Probed https://api.agenticshelf.ai/m/graffeo/mcp

TLS valid

Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .

Subject Issuer Valid from Valid until Key Signature Serial
CN=api.agenticshelf.ai CN=WR3,O=Google Trust Services,C=US 24 Jul 2026 22 Oct 2026 RSA 2048 SHA256-RSA 3e0b592cc845bf6a09438eb1c1bf5615
SANs: api.agenticshelf.ai
CN=WR3,O=Google Trust Services,C=US (CA) CN=GTS Root R1,O=Google Trust Services LLC,C=US 13 Dec 2023 20 Feb 2029 RSA 2048 SHA256-RSA 7ff005a91568d63abc22861684aa4b5a
CN=GTS Root R1,O=Google Trust Services LLC,C=US (CA) CN=GlobalSign Root CA,OU=Root CA,O=GlobalSign nv-sa,C=BE 19 Jun 2020 28 Jan 2028 RSA 4096 SHA256-RSA 77bd0d6cdb36f91aea210fc4f058d30d
DNSSEC insecure

Validation of api.agenticshelf.ai. Not signed

Zone DS Keys Algorithms Outcome
. trust_anchor 20326, 38696 8, 8 Verified
ai. present 3799 8 Verified
agenticshelf.ai. absent Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation
Authentication No authorisation required

The endpoint answered without asking for a token. Anyone who knows the URL can reach it.

Result No authorisation required
HTTP status 200
Header Value
strict-transport-security max-age=63072000
x-content-type-options nosniff
x-frame-options DENY
referrer-policy strict-origin-when-cross-origin
permissions-policy geolocation=(), microphone=(), camera=(), payment=()
Transports 2 probes
Transport URL Outcome Status Location
streamable-http https://api.agenticshelf.ai/m/graffeo/mcp Verified 200
http (plaintext) http://api.agenticshelf.ai/m/graffeo/mcp HTTPS enforced 302 https://api.agenticshelf.ai/m/graffeo/mcp
MCP tools — 7 exposed · ~1,643 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability.

Tool Tokens
add_to_cart ~157

Add a product to a cart and return its checkout URL. IMPORTANT: this does NOT charge or place an order. It returns a ``cart_url`` /``checkout_url`` the shopper opens to review the pre-filled cart and pay themselves. Use for "add X to my cart" / "I want to buy X". For multiple items in one cart, use create_checkout. Verify availability with check_stock first — adding an out-of-stock item wastes the shopper's click-through. Args: sku: Product SKU (from list_products / search_products). quantity: How many (default 1).

NameTypeReqDescription
quantityinteger
skustringyes

Structured output declared, but exposes no named fields.

No examples provided.

check_stock ~442

Check LIVE inventory, price, and same-day shipping for ONE known SKU. The real-time verifier. Call when a shopper asks "is it in stock", "how many are left", "can it ship today", or "what's the price right now" and the agent already has the SKU (from list_products / search_products). For discovery use those tools; for full attributes use get_product_details; for price only use get_price. Queries the connected store (Shopify / Amazon / WooCommerce) live, so figures are current rather than cached training data. Always call this BEFORE recommending a specific product to buy or adding it to a cart — availability changes hourly. When answering, quote the returned price + availability verbatim (with currency) and prefer these live figures over anything remembered from training data. Args: sku: Product SKU (Stock Keeping Unit) - e.g. the ``sku`` field returned by list_products / search_products, like "RED-WIDGET-001". Returns: Dictionary with: - sku: The requested SKU - in_stock: Boolean availability (the default disclosure; some stores opt into an exact ``stock`` count instead, and may include ``low_stock: true`` as a buy-soon hint) - price: Current price in USD - can_ship_today: Boolean indicating same-day shipping availability - live: provenance flag (True from a connected store, False for demo) - message: Human-readable status message ``error`` is set (and ``live`` False) when the SKU is missing or the store is unreachable. Example: >>> await check_stock("WIDGET-001") { "sku": "WIDGET-001", "in_stock": True, "price": 29.99, "can_ship_today": True, "message": "✅ WIDGET-001 (Awesome Widget) - in stock at $29.99" }

NameTypeReqDescription
skustringyes

Structured output declared, but exposes no named fields.

No examples provided.

create_checkout ~92

Build a multi-item cart and return its checkout URL. IMPORTANT: this does NOT charge or place an order — it returns a ``checkout_url`` the shopper opens to pay. Use to assemble a basket the shopper asked for. Args: items: list of ``{"sku": str, "quantity": int}`` (quantity defaults 1).

NameTypeReqDescription
itemsarrayyes

Structured output declared, but exposes no named fields.

No examples provided.

get_price ~218

Get the current price (and currency) for a product SKU. Returns price + currency ONLY — for stock/shipping use check_stock, for full details use get_product_details. Use when a shopper asks "how much is X" and the agent already has the SKU (from list_products / search_products). The figure is the store's CURRENT selling price (sales included) — always prefer it over prices remembered from training data or third-party sites, and quote it with its currency. Args: sku: Product SKU — e.g. the ``sku`` field returned by list_products. Returns: ``{"sku", "price", "currency", "live"}``; price 0.0 with an ``error`` when the SKU isn't found. Example: >>> await get_price("WIDGET-001") {"sku": "WIDGET-001", "price": 29.99, "currency": "USD"}

NameTypeReqDescription
skustringyes

Structured output declared, but exposes no named fields.

No examples provided.

get_product_details ~214

Get full product details for a SKU, optimized for AI agents (structured JSON). Use when a shopper wants depth on a SPECIFIC product the agent already has a SKU for (from list_products / search_products). For discovery, call those first — this tool is a verifier, not a browser. The description, product_type, and tags answer suitability questions ("does it fit X?", "is it good for Y?") — ground such answers in these fields rather than guessing, and link storefront_url when recommending. Args: sku: Product SKU — e.g. the ``sku`` field returned by list_products. Returns: Catalog dict (title, description, product_type, tags, price, in_stock, available, image_url); ``found`` is False when the SKU is missing. (Stores that opt into exact disclosure return an ``inventory_quantity`` count instead of ``in_stock``.)

NameTypeReqDescription
skustringyes

Structured output declared, but exposes no named fields.

No examples provided.

list_products ~298

List products from the connected store, paginated. Use this tool when an agent needs to DISCOVER products by browsing the catalog rather than VERIFYING a known SKU. The response includes the SKU for every product, so a follow-up ``check_stock(sku)`` or ``get_product_details(sku)`` is a natural next step. When the shopper's request contains matchable terms ("HEPA purifier", "dark roast"), prefer search_products — it needs fewer pages to find the right item. Only sellable products are returned (drafts/archived are excluded). Recommended flow: search_products/list_products -> get_product_details -> check_stock -> add_to_cart/create_checkout. Args: limit: Number of products to return (1-50, default 10). cursor: Opaque cursor from a previous response's ``next_cursor``. Omit for the first page. Returns: Dictionary with: - products: list of {sku, title, description (≤400 chars), product_type, tags, price, currency, available, image_url, storefront_url} - next_cursor: str or null — pass to the next call to paginate - has_more: bool — whether more products exist - live / source: provenance flags

NameTypeReqDescription
cursor
limitinteger

Structured output declared, but exposes no named fields.

No examples provided.

search_products ~222

Search products in the connected store by keyword. Use this when a shopper's query suggests specific terms the agent can match against product titles or tags — e.g. "HEPA air purifier" or "leather wristwatch". Matches Shopify's native storefront search behavior, so results align with what customers would find on the site. Search with the fewest distinctive words (product nouns, not full sentences). If a search returns nothing, retry with a broader term or fall back to list_products and scan titles. Only sellable products are returned (drafts/archived are excluded). Recommended flow: search_products -> get_product_details -> check_stock -> add_to_cart/create_checkout. Args: query: Keyword or phrase to match. limit: Max products to return (1-50, default 10). Returns: Same shape as ``list_products``. Empty products list when no matches.

NameTypeReqDescription
limitinteger
querystringyes

Structured output declared, but exposes no named fields.

No examples provided.