dominion-observatory
Dominion Observatory
Documentation
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_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 · 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
Frequently asked questions
What is dominion-observatory?
dominion-observatory is Dominion Observatory
How do I install dominion-observatory?
Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.
Is dominion-observatory open source?
Yes — it is hosted on GitHub at https://github.com/vdineshk/dominion-observatory and has 1 stars.
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