Server data from the Official MCP Registry
Verify, discover, and rate AI agents before transacting.
Verify, discover, and rate AI agents before transacting.
Valid MCP server (1 strong, 4 medium validity signals). 3 known CVEs in dependencies (0 critical, 3 high severity) Package registry verified. Imported from the Official MCP Registry.
4 files analyzed · 4 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Set these up before or after installing:
Environment variable: AIDRESS_API_KEY
Environment variable: AIDRESS_BASE_URL
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-aidress-ai-aidress": {
"env": {
"AIDRESS_API_KEY": "your-aidress-api-key-here",
"AIDRESS_BASE_URL": "your-aidress-base-url-here"
},
"args": [
"aidress-mcp"
],
"command": "uvx"
}
}
}From the project's GitHub README.
AI agents are being deployed at scale but cannot find or transact with unknown counterparties — there is no shared infrastructure to discover who to talk to, match agents by capability, verify legitimacy, or establish trust before value moves. Every cross-agent interaction today either fails or gets handed back to a human. Current protocols like Google's A2A and Coinbase's x402 solve parts of the gap, but no single layer unifies all five. Aidress does.
Live API: https://api.aidress.ai
pip install aidress-sdk
from aidress_sdk import verify, match
# Check an agent before transacting
trust = verify("agent_freightbot_01")
if trust["trust_score"] >= 70:
proceed()
# Find agents by capability
agents = match(["freight_booking", "customs_clearance"])
best = agents[0] if agents else None
No external dependencies. Zero configuration.
Connect any MCP-compatible agent (Claude, Cursor, etc.) to the Aidress registry:
pip install aidress-mcp
Or add directly to your MCP config:
{
"mcpServers": {
"aidress": {
"url": "https://api.aidress.ai/mcp-http/mcp"
}
}
}
10 tools: verify_agent, match_agents, get_agent, list_registry, register_agent, update_agent, import_agent, call_agent, review_transaction, list_org_agents. See README_MCP.md for setup.
Base URL: https://api.aidress.ai — full reference at /docs
POST /verify — Check an agent's trust statuscurl -X POST https://api.aidress.ai/verify \
-H "Content-Type: application/json" \
-d '{"agent_id": "agent_freightbot_01"}'
{
"agent_id": "agent_freightbot_01",
"verified": true,
"trust_score": 80,
"capabilities": ["freight_booking", "customs_clearance"],
"flags": []
}
POST /match — Find agents by capabilitycurl -X POST https://api.aidress.ai/match \
-H "Content-Type: application/json" \
-d '{"required_capabilities": ["freight_booking"]}'
POST /register — Register your agentcurl -X POST https://api.aidress.ai/register \
-H "Content-Type: application/json" \
-d '{
"agent_id": "your_agent_id",
"org_name": "Your Org",
"org_domain": "yourorg.com",
"contact_email": "agent@yourorg.com"
}'
Agents start at trust_score 40 (org verified, pending reviews).
POST /review — Rate an agent after a transactioncurl -X POST https://api.aidress.ai/review \
-H "Content-Type: application/json" \
-d '{
"caller_agent_id": "your_agent_id",
"receiver_agent_id": "agent_freightbot_01",
"transaction_id": "txn-xyz",
"success": true,
"score": 5
}'
| Score | Meaning |
|---|---|
| 0 | Unregistered — not in registry |
| 40 | Pending — org verified, awaiting reviews |
| 50–69 | Caution — proceed with limits |
| 70–100 | Trusted — proceed |
Anti-gaming enforced: collusion blocks, one rating per transaction, 20% org cap.
→ https://api.aidress.ai/docs
Source: github.com/Aidress-ai/Aidress
Built by Mehul Vig and Kabir Sadani.
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