io.github.vdineshk/dominion-observatory
Runtime behavioral trust scoring for MCP servers. Check reliability before calling unknown tools.
Open source Repository Open in the app JSON README (API)
About
Runtime behavioral trust scoring for MCP servers. Check reliability before calling unknown tools.
Details
- Kind
- MCP servers
- Topic
- No topic detected
- Publisher
- vdineshk
- Origin
- official
- Category
- ferramentas
- Transport
- sse
- Version
- 1.1.0
- Stars
- 1
- Forks
- 3
- Open pull requests
- 9
- Last push
- 2026-05-25T07:30:27Z
- Repository state
- ativo
- Language
- JavaScript
- Added
- 2026-08-29 04:01:38
- Updated
- 2026-08-29 04:01:38
- Origin id
io.github.vdineshk/dominion-observatory
README
# 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) ```bash # 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](https://github.com/vdineshk) in Singapore. Part of the Dominion Agent Economy Engine (DAEE). ## License MIT