scamgate
Offline scam check for agents: verify links and payments before acting (allow, ask or deny).
No outside reports on file
scamgate is distributed via PyPI (scamgate); review its source code, dependencies, and requested permissions before use.
Based on public adoption and transparency signals as of Oct 25, 2026. Our opinion, not a code audit or security guarantee.
What it can access
- Local filesNo local folder access notedLOW
- Command executionNo shell command runner notedLOW
- Network reachLocal or standard API callsLOW
- CredentialsNo API token requiredLOW
- Package sourcePyPI (scamgate)PUBLIC
Inferred from this listing’s public package details and description. Check the project’s source before installing.
Install
uvx scamgateAbout Scamgate
Scamgate is an MCP server focused on General: Offline scam check for agents: verify links and payments before acting (allow, ask or deny).
It is published on PyPI as scamgate and hosted on GitHub at odaiameera/scamgate. Based on its public metadata, it operates with standard local or API scope without broad shell execution flags noted.
Setup
These use the package this listing points to. Check the project’s own instructions before running anything.
PyPI command
uvx scamgatePyPI (pip) command
pip install scamgateMCP client config
For Claude Desktop (claude_desktop_config.json) or Cursor (.cursor/mcp.json).
{
"mcpServers": {
"scamgate": {
"command": "uvx",
"args": [
"scamgate"
]
}
}
}Why this grade
Signal-based grade (1/7 points): public source code. This reflects adoption and transparency, not a code review.
Popularity and upkeep
- Listing last refreshed
- 2026-10-29
These are public popularity signals, not a maintenance check. Look at the repository’s commit history and open issues.
Security reports
No reports found for this package in our research (last checked 2026-10-30).
Risks to watch for
- Dependency & version pinning: Distributed via PyPI (scamgate). Pin an exact release version or commit SHA rather than floating tags so upstream updates are reviewed first.
How to lower the risk
Least-privilege permissions
- Give it access only to the specific folders, accounts or projects it needs, never your whole drive or admin account.
- Use a separate, limited API key or login just for this tool so you can switch it off without affecting anything else.
Network isolation
- Run it on a work computer or sandbox account, not one holding personal or company-sensitive data.
- If your IT team can, limit which websites and services it is allowed to contact.
Monitoring
- Check its activity history or logs weekly at first, and look at what it changed or sent.
- Turn on alerts for new logins or unusual usage on any account it connects to.
Red flags to watch for
- It asks for more access than its job requires, or prompts you to paste passwords.
- It suddenly updates with new owners, or starts contacting unfamiliar websites.
Questions
How do I install Scamgate?
Run uvx scamgate (or pip install scamgate) in your terminal, or add the server entry to your claude_desktop_config.json or .cursor/mcp.json as shown in the Setup section on this page. Full setup docs and environment variables are in github.com/odaiameera/scamgate.
Are there security reports about Scamgate?
No reports found for this package in our research (last checked 2026-10-30). Scamgate currently holds Grade D (High risk signals) based on public adoption and transparency signals. Review the permissions and source repository before granting access to local files, shell commands, or API keys.
Is Scamgate actively maintained?
We do not have star or download counts on file for Scamgate yet (listing refreshed 2026-10-29). Check the commit history and open issues at github.com/odaiameera/scamgate before relying on it.
What are alternatives to Scamgate?
Compare Scamgate side by side with similar MCP servers in the Related tools section on this page, or browse all MCP servers on AgentArmorHQ.
Key facts
- Type
- App connector
- Publisher
- odaiameera
- Source code
- github.com/odaiameera/scamgate
- Install command
- pip install scamgate
- Est. context load
- ~850 tokens / turn (~5 tool schemas, 0.43% of 200k context)
- Last updated
- 2026-10-29
- Last graded
- 2026-10-26
Community
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