rugcheck-ai
Server Details
Solana token safety for AI agents — rug-pull, honeypot & Token-2022 trap detection before you buy.
- Status
- Unhealthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- MrWizardlyLoaf/rugcheck-ai
- GitHub Stars
- 1
- Server Listing
- RugCheck AI
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
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.
Tool Definition Quality
Average 4.1/5 across 15 of 15 tools scored. Lowest: 2.4/5.
Several tools overlap in purpose, particularly scan_token and verify_token_safety both offering a full safety verdict. Tools like is_safe, batch_scan, and compare_tokens also reuse aspects of the core scan, creating ambiguity about which to use for a given task.
Tool names are inconsistent in style: some use verb_noun (scan_token, simulate_sell), others are noun phrases (holders_breakdown, rug_forecast) or mixed (verify_token_safety, execute_safe_swap). Underscores are used sporadically, and names like 'scammer_dna' lack clarity.
With 15 tools focused on token safety analysis, the count is appropriate for covering various aspects without being overwhelming. The scope is well-defined, and each tool addresses a specific need, though some consolidation could reduce redundancy.
The server covers the full lifecycle of token safety analysis: scanning, specific checks (authorities, liquidity, holders), simulation, comparison, and forecasting. Minor gaps exist (e.g., no tool for retrieving basic token metadata), but the core safety workflow is well-supported.
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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