solrisk-mcp
Server Details
Solana token risk (rug / honeypot / dump) scoring for AI agents — remote MCP server.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- comil27/solrisk-mcp
- GitHub Stars
- 0
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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
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Managed credentials
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Usage analytics
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Tool Definition Quality
Average 4/5 across 1 of 1 tools scored.
Only one tool exists, so there is no ambiguity for the agent in selecting the correct tool.
With a single tool, naming is trivially consistent; the name clearly describes its function.
A single tool for Solana token risk scoring is minimal but borderline reasonable for a narrow domain; 1 tool feels thin.
The tool covers key on-chain risk signals (mint/freeze authority, holder concentration, liquidity, volume), adequately fulfilling its stated purpose without obvious gaps.
Available Tools
1 toolsolana_token_riskAInspect
Score the rug / honeypot / dump risk (0 = safe .. 100 = high risk) of any Solana SPL token from on-chain signals: mint & freeze authority, top-holder concentration, liquidity and volume. Returns JSON.
| Name | Required | Description | Default |
|---|---|---|---|
| mint | Yes | Solana SPL token mint address (base58, 32-44 chars) |
Tool Definition Quality
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 discloses that the tool uses on-chain signals and returns JSON. However, it does not mention behavioral traits like being read-only, rate limits, or authentication needs. It is adequate but minimal.
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 a single sentence that front-loads the key information (risk scoring) and efficiently explains inputs and outputs. No wasted words.
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's simplicity (one parameter, no output schema), the description is fairly complete. It explains the input and the output format (JSON with risk score). A more detailed output structure would be helpful but not essential.
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?
The input schema already provides a description for the 'mint' parameter (pattern and explanation). Schema coverage is 100%, so baseline is 3. The tool description does not add new parameter semantics beyond what the schema provides.
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's purpose: scoring rug, honeypot, and dump risk of Solana SPL tokens on a 0-100 scale. It specifies the on-chain signals used (mint & freeze authority, holder concentration, liquidity, volume) and that the output is JSON. This is specific and actionable.
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 implicitly tells when to use the tool: to assess the risk of any Solana SPL token. There are no sibling tools, so no need for exclusions. It provides clear context for usage.
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
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For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
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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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