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Glama

Server Details

MCP server for E-Commerce

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL

Glama MCP Gateway

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MCP client
Glama
MCP server

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Tool access control

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Managed credentials

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Usage analytics

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Tool DescriptionsD

Average 1.9/5 across 4 of 4 tools scored. Lowest: 1.3/5.

Server CoherenceB
Disambiguation3/5

get_e_commerce_data and list_e_commerce_items may overlap in functionality (both retrieve data), leading to potential confusion. health_check and search_e_commerce are distinct.

Naming Consistency3/5

Three tools use 'e_commerce' prefix with underscores, but health_check uses a different style (no prefix, camel case-like), creating inconsistency.

Tool Count4/5

4 tools is a reasonable size for a focused e-commerce server, though it leans toward the smaller side. Not excessive or insufficient.

Completeness2/5

The server lacks essential CRUD operations like create, update, delete for e-commerce items, as well as order management, making it incomplete for typical e-commerce workflows.

Available Tools

4 tools
get_e_commerce_dataDInspect

Tool: get_e_commerce_data. Uses: httpx public APIs. Price: ${PRICE_PER_CALL}/call

ParametersJSON Schema
NameRequiredDescriptionDefault
idYes
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It adds cost information ('Price: ${PRICE_PER_CALL}/call') but lacks details on side effects, return format, permissions, or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very short (two brief lines) but suffers from under-specification. Conciseness is not effective when critical information is omitted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of output schema, parameter documentation, and behavioral details, the description is severely incomplete. It does not help an agent understand what the tool does or how to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single required parameter 'id' has no explanation in the schema or description. With 0% schema description coverage, the description should compensate but fails to add any meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description mentions 'get_e_commerce_data' but does not specify what data is retrieved. It says 'Uses: httpx public APIs' which is vague. There is no differentiation from sibling tools like list_e_commerce_items or search_e_commerce.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. No exclusions or prerequisites are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

health_checkCInspect

Health check.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description carries full burden for behavioral disclosure. 'Health check' does not describe what happens on success/failure, response format, side effects, or any other behavioral traits, which is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely brief (two words) and front-loaded, but it sacrifices essential information. It is concise but under-specified for a tool that likely has important behavior to convey.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no parameters, no output schema, and a simple purpose, the description is still incomplete. It lacks details about expected return values, status codes, or error conditions, which are crucial for a health check tool.

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?

There are zero parameters and 100% schema description coverage. The description adds no extra meaning beyond the schema. Per guidelines, baseline is 3 when coverage is high, and there is no additional value, so score 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Health check.' states the tool's general purpose but is vague. It does not specify what system or component is being checked or what condition 'healthy' means, leaving the agent with minimal understanding.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No usage guidelines provided. The description gives no context on when to use this tool versus sibling tools (which are e-commerce focused), nor any prerequisites or scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_e_commerce_itemsDInspect

Tool: list_e_commerce_items. Uses: httpx public APIs. Price: ${PRICE_PER_CALL}/call

ParametersJSON Schema
NameRequiredDescriptionDefault
filtersYes
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, and the description fails to disclose any behavioral traits (e.g., read vs write, side effects, permissions). The only additional info is pricing, which is not behavioral.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

While brief, the description omits essential information. Conciseness should not come at the expense of completeness; the description is too short to be helpful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (nested parameter, no output schema, no annotations), the description is completely insufficient. It lacks details about return values, behavior, and parameter semantics.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has one required parameter 'filters' (object with additionalProperties true) with 0% schema description coverage. The description provides no explanation of the filter structure or expected format, forcing the AI to guess.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description only repeats the tool name and mentions 'httpx public APIs' without specifying what the tool lists or does. It does not clarify the scope or differentiate from siblings like search_e_commerce.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No usage guidelines are provided. There is no indication of when to use this tool vs alternatives like get_e_commerce_data or search_e_commerce.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_e_commerceCInspect

Tool: search_e_commerce. Uses: httpx public APIs. Price: ${PRICE_PER_CALL}/call

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYes
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. Discloses use of httpx public APIs and price, but does not mention if it is read-only, what data it returns, or any side effects. Minimal behavioral insight.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is very short (two sentences) but front-loads technical implementation details (httpx, price) which are less relevant than functional purpose. Could be restructured to first state what the tool does.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and one parameter, the description is insufficient. It does not explain the search behavior, return values, or how to effectively use the tool. Agent lacks sufficient context for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%; description does not explain the single required 'query' parameter. No examples or expected format provided, leaving agent without context on how to construct the query.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description states it's a search tool for e-commerce and uses httpx public APIs, but does not specify what exactly it searches (products, data, etc.). It distinguishes itself from siblings only by name, not by function.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus siblings like list_e_commerce_items or get_e_commerce_data. Only mentions price per call, which is a cost consideration but not usage context.

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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