Scern
Server Details
Product evaluation MCP server for US packaged food. Health scores, ingredient safety, regulatory flags, recall history, corporate ownership.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Score is being calculated. Check back soon.
Available Tools
2 toolscompare_productsCompare ProductsRead-onlyInspect
Compare 2–5 products by health score. Returns all evaluations, a ranking by health score (descending), and the best-scoring barcode. Products not found are included as { value, status: 'not_found' } and excluded from the ranking.
| Name | Required | Description | Default |
|---|---|---|---|
| values | Yes | Array of 2–5 barcode values to compare | |
| context | No | Evaluation context (default: retail) | |
| identifier | No | Barcode identifier type, applied to all values | upc |
| jurisdiction | No | Filter regulatory flags: CA, TX, or WV |
evaluate_productEvaluate ProductARead-onlyInspect
Evaluate a product's health score, ingredient safety, corporate ownership, and regulatory flags using the Scern database. Pass a UPC or EAN barcode value.
| Name | Required | Description | Default |
|---|---|---|---|
| value | Yes | Barcode value | |
| context | No | Evaluation context (default: retail) | |
| identifier | Yes | Barcode identifier type | |
| jurisdiction | No | Filter regulatory flags by jurisdiction. Valid values: CA, TX, WV |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, non-destructive operation. Description adds that it uses Scern database and lists evaluation aspects, but no additional behavioral traits like latency, data freshness, or error handling are disclosed.
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 sentences, front-loaded with purpose. No wasted words. Efficiently conveys what the tool does and how to use it.
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?
Given no output schema, description covers what the tool evaluates (health, safety, ownership, flags). Could mention required parameters or expected output format more explicitly, but sufficient for a read-only tool with annotations.
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%, so baseline of 3 is appropriate. Description mentions 'UPC or EAN barcode value' which aligns with identifier and value parameters, but does not add meaning beyond the schema.
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?
Description clearly states verb 'evaluate', specific resource 'product', and lists health score, ingredient safety, corporate ownership, and regulatory flags. Distinguishes from sibling 'compare_products' by focusing on a single product evaluation.
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?
Description explains when to use (evaluating a product) but does not explicitly state when not to use or provide alternatives. Sibling tool 'compare_products' is a logical alternative for comparison tasks.
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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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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