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Sol MCP — Solana Token Risk & Signals

Sol MCP — Solana Token Risk & Signals

by autonsol
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

get_graduation_signals

Read-onlyIdempotent

Retrieve recent BUY or SKIP signals for pump.fun tokens at graduation, showing risk scores and momentum analysis to identify vetted trading opportunities.

Instructions

Get recent token graduation signal decisions from Sol's on-chain analysis engine. Shows which pump.fun tokens were flagged as BUY or SKIP, with full reasoning. Tokens are evaluated at graduation (bonding curve completion) using risk score + momentum. BUY signals have risk ≤65 and strong momentum (2.0–3.0× ratio depending on risk tier). Use this to discover tokens Sol's AI has vetted as worth trading.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_graduation_signals"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoNumber of recent decisions to return (1–50). Default: 10.
filterNoFilter by decision type: 'trade' (BUY signals only), 'skip' (filtered out), or 'all'.all

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.3.0

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true, and idempotentHint=true. The description adds useful context about the evaluation criteria (risk score + momentum) and signal thresholds, but does not disclose rate limits, authentication needs, or pagination behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded with the core purpose. All sentences add value, though the second sentence could be slightly more concise by integrating the evaluation criteria more smoothly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity, rich annotations, and 100% schema coverage, the description is mostly complete. It explains the purpose and usage context well, but lacks details on output format or error handling, which would be helpful since there is no output schema.

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?

Schema description coverage is 100%, so the schema fully documents both parameters. The description implies filtering by BUY/SKIP decisions but does not add syntax or format details beyond what the schema provides, meeting the baseline for high coverage.

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 clearly states the specific action ('Get recent token graduation signal decisions'), resource ('from Sol's on-chain analysis engine'), and scope ('pump.fun tokens'). It distinguishes from siblings by focusing on graduation decisions with BUY/SKIP signals, unlike risk or momentum tools.

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool ('to discover tokens Sol's AI has vetted as worth trading'), but does not explicitly state when not to use it or name specific alternatives among the sibling tools.

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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