scamcheck-mcp-server
Server Details
Scan suspicious messages, URLs, and text for scams with AI. Free tier - no API key required.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- smijo-geek/scamcheck-mcp-server
- GitHub Stars
- 0
- Server Listing
- ScamCheck MCP Server
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Full call logging
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Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4.5/5 across 1 of 1 tools scored.
Only one tool exists, so there is no possibility of confusion between tools.
The single tool uses a clear verb_noun pattern (scan_message), which is consistent and descriptive.
With only one tool, the server feels underdeveloped for a scam-checking service, missing related functionality like history or batch processing.
The server only provides a single scan action, lacking any additional operations (e.g., report history, multiple scan types) that would make it a comprehensive scam-checking tool.
Available Tools
1 toolscan_messageARead-onlyIdempotentInspect
Scan a suspicious message, URL, or text for scam indicators using ScamCheck AI. Returns a verdict (Likely Scam / Suspicious / Likely Safe), risk score 0-100, category, confidence percentage, reasons flagged, and recommended actions. Use this whenever a user shares a message they received and wants to know if it's a scam.
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | The message, URL, or text to scan. Minimum 8 characters. | |
| source | No | Content type: text (default), url, or screenshot. | text |
Output Schema
| Name | Required | Description |
|---|---|---|
| risk | Yes | Overall risk level: high, medium, or low |
| score | Yes | Risk score from 0 (safe) to 100 (certain scam) |
| reasons | Yes | Why this was flagged |
| summary | Yes | 1-2 sentence analysis |
| verdict | Yes | Likely Scam | Suspicious | Likely Safe |
| category | No | Scam category, e.g. phishing, lottery_scam, job_scam |
| confidence | No | Confidence percentage 0-99 |
| next_steps | No | What the user should do now |
| result_url | No | Shareable full-report URL |
| recovery_steps | No | Steps if the user already fell for it |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds detail on return values (verdict, risk score, etc.) and the general behavior. There is no contradiction, and the description complements annotations well.
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?
The description is two sentences: the first explains functionality and output, the second provides usage guidance. It is concise, front-loaded, and every sentence is valuable.
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 the tool has an output schema and the description lists the return fields, the description provides sufficient context for a user to understand the tool's purpose and when to use it. There are no missing aspects for a scanning tool.
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%, and both parameters are already described in the schema. The description's mention of 'message, URL, or text' aligns with the input parameter but does not add significant new meaning beyond the schema definitions.
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 the tool scans suspicious messages, URLs, or text using ScamCheck AI and lists specific outputs. It uses a specific verb 'scan' and resource description, and with no sibling tools, there is no differentiation needed.
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 explicitly states when to use the tool: 'Use this whenever a user shares a message they received and wants to know if it's a scam.' This provides clear context with no ambiguity or need for alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$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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For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
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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