Agent Insurance

MCP server for AI agent transaction insurance and escrow — protect agent-to-agent payments with smart escrow, dispute resolution, and risk scoring.

PyPI version License: MIT

What it does

When AI agents transact with each other — paying for data, code, analysis, or content — there's no guarantee of delivery. This server adds a trust layer:

1. Buyer agent creates an escrow → funds are locked
2. Seller agent completes the task
3. Buyer agent releases escrow → seller receives payment
4. If something goes wrong → dispute opens, auto-verdict runs

Tools (11)

Tool	Description
create_escrow	Lock funds between buyer/seller agent for a task
release_escrow	Release funds after task completion (success/partial)
open_dispute	Open a dispute if something goes wrong
get_insurance_quote	Get risk score + premium before transacting
process_claim	Resolve a dispute (buyer_wins/seller_wins/split)
get_escrow_status	Check current status and all details of an escrow
get_insurance_info	System stats: active escrows, disputes, protected amounts
list_escrows	NEW Browse and filter all escrows (by status, agent, etc.)
get_agent_history	NEW Full transaction history + trust score for any agent
auto_resolve_expired	NEW Automatically resolve expired escrows (buyer refund)
insurance_analytics	NEW System analytics: volume, risk distribution, top agents

Installation

pip install agent-insurance-mcp-server

Claude Desktop Configuration

{
  "mcpServers": {
    "agent-insurance": {
      "command": "agent-insurance-mcp-server"
    }
  }
}

Example Usage

# 1. Get a quote first
quote = get_insurance_quote(
    buyer_agent_id="agent_buyer_001",
    seller_agent_id="agent_coder_007",
    amount=100.0,
    task_type="code"
)
# → risk_score: 35, premium: 2.8%, premium_amount: 2.80

# 2. Create escrow
escrow = create_escrow(
    buyer_agent_id="agent_buyer_001",
    seller_agent_id="agent_coder_007",
    amount=100.0,
    task_description="Build a REST API endpoint for user authentication",
    deadline_hours=48
)
# → escrow_id: "escrow_abc123def456", status: "active"

# 3a. Release on success
result = release_escrow(
    escrow_id="escrow_abc123def456",
    outcome="success"
)
# → seller_payout: 100.0, buyer_refund: 0.0

# 3b. Or open a dispute
dispute = open_dispute(
    escrow_id="escrow_abc123def456",
    reason="Task not delivered as agreed — API is missing auth logic"
)
# → auto_verdict: "buyer_favored", buyer_protection: 80%

# 4. Check agent trust (NEW in v0.2.0)
history = get_agent_history(agent_id="agent_coder_007")
# → trust_score: 72, completion_rate: 90%, dispute_rate: 5%

How Risk Scoring Works

• Base risk: 30 points
• Seller dispute history: +0-40 points based on past disputes
• Transaction size: +5-15 points for large amounts
• Experience bonus: -2 points per completed escrow (max -20)
• Premium range: 1-5% of transaction amount

Changelog

v0.2.0 (April 2026)

• 4 new tools: list_escrows, get_agent_history, auto_resolve_expired, insurance_analytics
• Agent trust scoring (0-100) based on transaction history
• Expired escrow auto-resolution with buyer refund
• System-wide analytics (volume, risk distribution, top agents)
• 11 tools total (up from 7)

v0.1.0

• Initial release with 7 core tools

Related MCP Servers

• agent-staking-mcp-server — Agent reputation staking
• agent-reputation-mcp-server — Agent trust scores
• x402-mcp-server — Agent micropayments

License

MIT — built by AiAgentKarl