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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 šŸ“” 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_trust tells you if it's reliable

  • After calling any MCP server → report_interaction contributes 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 Ā· finance Ā· code Ā· data Ā· search Ā· compliance Ā· transport Ā· productivity Ā· communication

Operator

Built by Dinesh Kumar in Singapore. Part of the Dominion Agent Economy Engine (DAEE).

License

MIT

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security - not tested
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license - not found
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quality - not tested

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