Skip to main content
Glama

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

F
license - not found
-
quality - not tested
C
maintenance

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/vdineshk/dominion-observatory'

If you have feedback or need assistance with the MCP directory API, please join our Discord server