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Glama

Double Check

Server Details

AI-powered scam detection for suspicious texts, emails, and screenshots. US-focused.

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL

Glama MCP Gateway

Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.

MCP client
Glama
MCP server

Full call logging

Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.

Tool access control

Enable or disable individual tools per connector, so you decide what your agents can and cannot do.

Managed credentials

Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.

Usage analytics

See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.

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Tool DescriptionsA

Average 3.9/5 across 1 of 1 tools scored.

Server CoherenceA
Disambiguation5/5

Only one tool exists, so there is no ambiguity between tools.

Naming Consistency5/5

With a single tool named 'check', naming is consistent and clear.

Tool Count2/5

A single tool is too few for a scalable server; agents may need distinct tools for different input types or actions.

Completeness5/5

The tool covers all common scam-checking needs (messages, URLs, emails, text) and returns comprehensive results.

Available Tools

1 tool
checkAInspect

Check whether a message, URL, email, or piece of text is a scam. Returns a verdict (safe/scam/action/ignore), a plain-English summary, recommended next steps, and a confidence level.

ParametersJSON Schema
NameRequiredDescriptionDefault
contentYesThe message text, URL, or email content to analyze. Max 5000 characters.
input_typeNoWhether the content is plain text or a URL. Defaults to 'text'.
Behavior3/5

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

No annotations exist, so the description carries full burden. It adds value by describing the return format (verdict, summary, next steps, confidence), but it does not disclose potential side effects, error behavior, or authentication requirements. The description is adequate but incomplete for full transparency.

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?

The description is a single sentence that front-loads the core purpose ('Check whether...') and efficiently lists return elements. Every word adds value, with no redundant or extraneous information.

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 simplicity (2 params, no output schema, no siblings), the description is fully complete. It clearly states what the tool does, what inputs to provide, and what outputs to expect. No additional context is needed.

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?

Input schema coverage is 100%, so baseline is 3. The description does not add new information beyond what the schema already provides (e.g., max characters, input_type enum). It repeats the schema descriptions without enhancing semantic understanding.

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 uses a specific verb ('Check whether') and clearly identifies the resource (scams on messages, URLs, emails, or text). It also lists the return elements (verdict, summary, next steps, confidence), leaving no ambiguity about the tool's purpose.

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

Usage Guidelines3/5

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

The description states the tool is for checking scam content but does not provide explicit guidance on when to use it versus alternatives. Since there are no sibling tools, the lack of differentiation is less critical, but no usage context or exclusions are given.

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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