Dominion Observatory
The behavioral trust layer for the AI agent economy.
Check MCP server reliability before you call. Report outcomes to strengthen the trust network.
🌐 Live: https://dominion-observatory.sgdata.workers.dev 📡 MCP Endpoint: https://dominion-observatory.sgdata.workers.dev/mcp
What is this?
Every AI agent needs to know: "Can I trust this MCP server?" The Dominion Observatory answers that question with real runtime data — not GitHub stars, not static scans, but actual performance metrics from real agent interactions.
- Before calling an unknown MCP server →
check_trusttells you if it's reliable - After calling any MCP server →
report_interactioncontributes to the trust network - Every report makes scores better for everyone — this is a collective intelligence system
Tools (8)
| Tool | Description |
|---|---|
check_trust | Get trust score and reliability metrics for any MCP server |
report_interaction | Report success/failure after calling an MCP server |
get_leaderboard | Top-rated MCP servers by category |
get_baselines | Behavioral baselines for a tool category |
check_anomaly | Is this server behavior normal or anomalous? |
register_server | Register a new MCP server (free) |
get_server_history | 30-day trust score trend for a server |
observatory_stats | Overall network statistics |
Quick Start
For agents (MCP)
Connect to: https://dominion-observatory.sgdata.workers.dev/mcp
For developers (REST API)
# Check trust score
curl "https://dominion-observatory.sgdata.workers.dev/api/trust?url=https://example.workers.dev/mcp"
# View leaderboard
curl "https://dominion-observatory.sgdata.workers.dev/api/leaderboard"
# Network stats
curl "https://dominion-observatory.sgdata.workers.dev/api/stats"
How Trust Scores Work
Trust scores range from 0-100 and combine two signals:
- Static score (30%): GitHub presence, documentation quality, authentication support
- Runtime score (70%): Real success rates, latency, error patterns from agent interactions
Scores above 70 = reliable. Below 30 = risky. The more agents report interactions, the more accurate scores become.
Architecture
- Runtime: Cloudflare Workers (330+ global edge locations, <1ms cold start)
- Database: Cloudflare D1 (SQLite at the edge)
- Protocol: MCP (Model Context Protocol) + REST API
- Cost: Runs on free tier
Data Collection
Started: April 8, 2026
Every interaction reported to the observatory strengthens the trust network for all agents. The behavioral dataset compounds daily — it cannot be replicated by competitors who start later.
Categories
weather · finance · code · data · search · compliance · transport · productivity · communication
Operator
Built by Dinesh Kumar in Singapore. Part of the Dominion Agent Economy Engine (DAEE).
License
MIT