Read a buyer's public buying preferences, forwarded to their buyer MCP. Pass the buyer_mcp_url from a find_buyers result. Delegation caps and private notes are never exposed.
| Name | Required | Description | Default |
|---|---|---|---|
| buyer_mcp_url | Yes | A buyer's mcp_url from a find_buyers result (…/buyers/{handle}/mcp). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that delegation caps and private notes are never exposed, and implies a read operation (no mutation). This adds important behavioral context beyond just stating it's a read.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-load the purpose and essential usage. Every sentence adds value: first explains what it does, second gives usage and a caveat. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description is complete enough. It covers purpose, usage, and a key behavioral limitation. A minor gap is not describing the response structure, but without output schema, this is acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter. The description reinforces the schema's instruction ('Pass the buyer_mcp_url from a find_buyers result') but does not add new meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Read a buyer's public buying preferences', specifying the verb (read) and the resource (buyer preferences). It distinguishes from siblings like get_buyer_briefs by focusing on preferences and mentioning forwarding to the buyer MCP.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit context: 'Pass the buyer_mcp_url from a find_buyers result', guiding when to use it. It does not explicitly exclude alternatives, but the instruction is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes (discovery, purchasing, negotiation, seller management, taste/intent). Some overlap exists, e.g., multiple ways to get product details, but descriptions clarify distinct use cases. A few tools like find_buyers and get_buyer_briefs might be confused at first glance but have different inputs.
Tool names predominantly follow verb_noun pattern in snake_case, e.g., find_seller, buy_product, get_shipping_quote. The outlier is seller_mcp_url which starts with a noun instead of a verb, and negotiate is a bare verb but fits. Overall consistent with minor deviations.
28 tools is on the high side for a single server, but the domain is complex (agentic commerce covering discovery, purchasing, negotiation, seller registration, etc.). The count is borderline heavy but reasonable for the breadth of functionality.
The tool set covers major aspects of agentic commerce: search, buying, negotiation, shipping, digital delivery, seller onboarding, and taste/intent. Missing features like order tracking or store updates are minor gaps; core workflows are well-supported.
