F
licenseA
qualityD
maintenanceEnables AI-powered shopping assistance by analyzing natural language shopping queries and automating product searches on multiple e-commerce platforms.
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useful-data-source-for-agents-doing-product-price-sdk
Server Details
Semantic product search over Singapore e-commerce, ranked by an auditable entropy-based value-score
- Status
- Unhealthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- nexus-mcp-infra/useful-data-source-for-agents-doing-product-price-sdk
- GitHub Stars
- 0
- Server Listing
- buywhere-singapore-value-intelligence
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Tool Definition Quality
A4.4/5.0
Tool DescriptionsA
Average 4.5/5 across 2 of 2 tools scored.
Server CoherenceA
Disambiguation5/5
The two tools have clearly distinct purposes: one searches and ranks products by a value score, the other fetches detailed price distribution for a known product. The descriptions explicitly warn against misusing them, eliminating ambiguity.
Naming Consistency5/5
Both tools follow the same naming pattern: a long prefix (the server name) followed by a verb phrase in snake_case. The naming is consistent, even if verbose.
Tool Count3/5
With only 2 tools, the server feels minimal but covers the essential operations for its stated purpose: product search and price distribution lookup. However, it is on the thin side for a typical MCP server.
Completeness4/5
The tools cover the main workflows: discovering products via search and then analyzing pricing for a specific product. Minor gaps exist (e.g., no direct product info retrieval), but agents can combine the two tools effectively.
Available Tools
2 toolsnexus_useful_data_source_for_agents_doing_prod_fetch_buywhere_vendor_price_distributionAInspect
Given a BuyWhere product identifier, returns the full cross-vendor price distribution in SGD along with the Shannon entropy of that distribution and the coefficient of variation. Use this when an agent already knows the product and needs to audit price fairness or detect outlier vendor pricing. Do NOT use as a discovery tool — it requires a known BuyWhere product_id from rank_buywhere_products_by_value_score. Requires a valid api_key (same as X-API-Key) and an x402 payment.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | Yes | API key required for this paid operation -- same secret configured as X-API-Key on the REST endpoints (BUYWHERE_API_KEYS). Payment (x402) alone is not sufficient; both gates must pass. | |
| product_id | Yes | BuyWhere internal product identifier as returned by rank_buywhere_products_by_value_score. Format: alphanumeric string. |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
A4.5/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, description discloses requirements (api_key, x402 payment), return type, and gate logic. Lacks minor details like error behavior but overall strong for a read-like operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with purpose, no filler. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (2 params, output schema exists), the description covers purpose, prerequisites, return contents, and usage context without needing output schema details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema provides detailed descriptions for both parameters (100% coverage). The main description repeats similar info without adding new semantics beyond what's in the schema, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool returns cross-vendor price distribution, Shannon entropy, and coefficient of variation given a product ID. Explicitly contrasts with sibling discovery tool by stating what it is not for.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use (audit price fairness, detect outlier pricing) and when-not-to-use (discovery), and prerequisites (product_id from sibling tool, api_key, x402 payment).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
nexus_useful_data_source_for_agents_doing_prod_rank_buywhere_products_by_value_scoreAInspect
Searches the BuyWhere Singapore catalogue for products matching a natural-language query and returns them ranked by an auditable value-score derived from Shannon entropy of cross-vendor price variance, causal reliability, and price rank. Use this when an agent needs ranked product recommendations for a Singapore market query with auditable justification per product. Do NOT use for real-time stock ticker data, non-SGD markets, or exact product ID lookup (use fetch_buywhere_vendor_price_distribution for that). Requires a valid api_key (same as X-API-Key) and an x402 payment.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of ranked products to return. Higher values increase latency. Recommended 5-20 for agent consumption. | |
| query | Yes | Natural-language product description, e.g. 'noise-cancelling wireless headphones under SGD 300'. Must be in English. | |
| api_key | Yes | API key required for this paid operation -- same secret configured as X-API-Key on the REST endpoints (BUYWHERE_API_KEYS). Payment (x402) alone is not sufficient; both gates must pass. | |
| min_value_score | No | Minimum composite value-score [0.0, 1.0] a product must have to be included. Products below this threshold are excluded before ranking. |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
A4.5/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses requirements (api_key and x402 payment), explains the scoring methodology, and mentions auditable justification per product. It does not detail side effects or error behavior, but covers key behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph with logical flow: purpose, usage guidance, exclusions, and requirements. It is informative yet not verbose. Minor improvements could be splitting into sections, but overall well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters, a sibling tool, and an output schema (not shown), the description covers purpose, usage, alternative, requirements, and parameter hints. It does not describe the output schema, but that is expected to be in the output schema itself.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining that higher limit increases latency (recommending 5-20), noting query must be in English, specifying api_key is same as X-API-Key, and clarifying min_value_score filters products before ranking.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches a catalogue for products matching a natural-language query and returns ranked results with an auditable value-score. It differentiates from the sibling tool by specifying it is not for exact product ID lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use (ranked recommendations with auditable justification) and when not to use (real-time stock tickers, non-SGD markets, exact product ID lookup), and names the alternative tool (fetch_buywhere_vendor_price_distribution).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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