verdictswarm-mcp 0.1.5

Fight AI with AI. The security layer for AI agents that touch money — 6 adversarial AI agents debate crypto token risk before your agent trades. Rug-pull detection, security audits, consensus scoring.

🔍 VerdictSwarm MCP Server

Fight AI with AI. Scammers build rugs with AI. Your agent catches them with 6.

The security layer for AI agents that touch money. One tool call between your trading agent and a rug pull.

Works with Claude Desktop, OpenClaw, Cursor, Codex, Windsurf, and any MCP-compatible client.

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Why?

AI trading agents are making autonomous on-chain decisions with zero risk analysis. Scammers are using AI to build increasingly sophisticated rugs that bypass single-algorithm scanners. The agent attack surface is the new phishing — but worse, because agents have system access and make financial decisions autonomously.

VerdictSwarm deploys 6 adversarial AI agents that independently analyze, debate, and reach consensus on any token:

• Adversarial debate — not one model's opinion. Six agents argue, including a Devil's Advocate that challenges every verdict. You see the dissenting opinions.
• On-chain security audits — mint authority, freeze authority, honeypot detection, LP lock status
• Rug pull detection — holder concentration, bundle/sniper activity, contract age analysis
• Agent-native — built for MCP. One tool call. Sub-second cached responses. No blockchain node required.

Quick Start

Install & Run

# Install from PyPI (recommended)
pip install verdictswarm-mcp
VS_API_KEY=your_key verdictswarm-mcp

# Or install from GitHub
pip install git+https://github.com/vswarm-ai/verdictswarm.git#subdirectory=mcp-server
VS_API_KEY=your_key verdictswarm-mcp

# Or with uvx (zero-install)
VS_API_KEY=your_key uvx git+https://github.com/vswarm-ai/verdictswarm.git#subdirectory=mcp-server

# Or clone and run
git clone https://github.com/vswarm-ai/verdictswarm.git
cd verdictswarm/mcp-server
uv run verdictswarm-mcp

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "verdictswarm": {
      "command": "uvx",
      "args": ["git+https://github.com/vswarm-ai/verdictswarm.git#subdirectory=mcp-server"],
      "env": {
        "VS_API_KEY": "your_key_here"
      }
    }
  }
}

Then ask Claude: "Check if this token is safe: DezXAZ8z7PnrnRJjz3wXBoRgixCa6xjnB7YaB1pPB263 on Solana"

OpenClaw

mcpServers:
  verdictswarm:
    command: uvx
    args: ["verdictswarm-mcp"]
    env:
      VS_API_KEY: your_key_here

No API Key?

The server works without a key at free-tier limits (10 scans lifetime, basic scores only). Get a key at vswarm.io for full access.

Tools

Tool	Description	Use When
scan_token	Full 6-agent consensus analysis	Deep due diligence on a specific token
get_quick_score	Fast cached score lookup (0-100)	Quick check before buying
check_rug_risk	Focused security/rug assessment	"Is this a scam?"
get_trending_risky	Trending high-risk tokens	Market surveillance (coming soon)
get_token_report	Formatted markdown report	Sharing analysis with others

Example: Quick Score

User: What's the risk score for BONK?
Agent: [calls get_quick_score("DezXAZ8z7PnrnRJjz3wXBoRgixCa6xjnB7YaB1pPB263")]
→ Score: 74/100 (Grade B) — LOW-MEDIUM risk

Example: Rug Check

User: Is this new memecoin safe? 7xKXtg2CW87d97TXJSDpbD5jBkheTqA83TZRuJosgAsU
Agent: [calls check_rug_risk("7xKXtg...")]
→ DANGER
  🚨 Liquidity NOT burned or locked
  ⚠️ Mint authority active
  ⚠️ Token is less than 24 hours old
  ⚠️ Bundle/sniper activity detected

Resources & Prompts

Resources (reference data for agents):

• verdictswarm://help — Tool usage guide
• verdictswarm://scoring — Score interpretation (0-100 scale, grades A-F)

Prompts (pre-built workflows):

• should_i_buy(token_address) — Full investment analysis with recommendation
• portfolio_check(tokens) — Batch risk assessment across holdings

Supported Chains

Chain	Status
Solana	✅ Full support
Ethereum	✅ Full support
Base	✅ Full support
BSC	✅ Full support

Scoring Guide

Score	Grade	Risk Level	Meaning
80-100	A	LOW	Relatively safe, established project
70-79	B	LOW-MEDIUM	Minor concerns, generally okay
60-69	C	MEDIUM	Proceed with caution
40-59	D	HIGH	Significant red flags
0-39	F	CRITICAL	Likely scam or rug pull

Configuration

Environment Variable	Default	Description
VS_API_KEY	(empty — free tier)	Your VerdictSwarm API key
VS_API_URL	https://api.vswarm.io	API base URL
VS_TIMEOUT	120	Request timeout in seconds

Architecture

MCP Client (Claude, Cursor, OpenClaw, Codex...)
    │
    │  MCP Protocol (stdio)
    ▼
┌──────────────────────────┐
│  VerdictSwarm MCP Server │  ← This package (thin wrapper)
│  FastMCP + Python        │
└──────────┬───────────────┘
           │  HTTP (httpx)
           ▼
┌──────────────────────────┐
│  VerdictSwarm API        │  ← api.vswarm.io
│  6 AI agents + on-chain  │
└──────────────────────────┘

The MCP server is a stateless wrapper — all intelligence lives in the VerdictSwarm API. This means:

• Lightweight deployment (no GPU, no blockchain node)
• Single source of truth for scan logic
• API-level rate limiting and caching already work

Development

git clone https://github.com/vswarm-ai/verdictswarm.git
cd verdictswarm/mcp-server
pip install -e ".[dev]"
pytest  # 47 tests, ~0.3s

License

MIT — see LICENSE.

Links

• Website: vswarm.io
• API Docs: api.vswarm.io/docs
• GitHub: vswarm-ai/verdictswarm
• MCP Spec: modelcontextprotocol.io

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Built by Sentien Labs — AI-operated crypto intelligence infrastructure.