Is Dominion Observatory free?

Yes, Dominion Observatory is free to use.

How do I install Dominion Observatory?

Dominion Observatory supports both local and remote installation. For local use, install it via the provided package manager and add the configuration to your AI app. For remote access, add the server URL to your MCP configuration.

Is Dominion Observatory safe to use?

Dominion Observatory scored 6.5/10 (moderate risk) in MCP Marketplace's automated security scan. It's listed, but review the security report on this page before installing.

What AI apps work with Dominion Observatory?

Dominion Observatory uses the Model Context Protocol (MCP) and works with any MCP-compatible AI app, including Claude, ChatGPT / Codex, Gemini, Copilot, Cursor, and more.

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Dominion Observatory MCP Server

by Vdineshk

Developer ToolsModerate6.5MCP RegistryLocalRemote

Free

Server data from the Official MCP Registry

Runtime behavioral trust scoring for MCP servers. Check reliability before calling unknown tools.

About

Runtime behavioral trust scoring for MCP servers. Check reliability before calling unknown tools.

Remote endpoints: streamable-http: https://dominionobservatory.com/mcp

Security Report

6.5

Moderate6.5Moderate Risk

The Dominion Observatory GitHub Action and README describe a trust-scoring service that reads local MCP config files and sends server identifiers (URLs, package names, commands) to an external API at dominionobservatory.com. The code is largely a benign, well-structured HTTP client with no hardcoded secrets or shell execution, but the README advertises a 'collective intelligence' system that collects every agent interaction, and the truncated code and scanner-flagged data-exfiltration tool names (get_news, bind_email, get_my_plan, etc.) warrant verification that no user data beyond public identifiers is transmitted. Score is moderated by undisclosed data-collection scope and by the server's reach into local config files.

4 files analyzed · 7 issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

File System Read

Reads files on your machine. Normal for tools that analyze or process local data.

HTTP Network Access

Connects to external APIs or services over the internet.

env_vars

Check that this permission is expected for this type of plugin.

How to Install & Connect

Available as Local & Remote

This plugin can run on your machine or connect to a hosted endpoint. during install.

Documentation

View on GitHub

From the project's GitHub 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://dominionobservatory.com 📡 MCP Endpoint: https://dominionobservatory.com/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 (14)

Tool	Description
`check_trust`	Get the trust score and reliability metrics for any MCP server. Use this BEFORE calling an unknown MCP server to assess if it's reliable. Returns trust_score (0-100), latency stats, uptime, success rate, and how many agents have used it. Scores above 70 indicate reliable servers. Scores below 30 indicate risky servers.
`clawhub_skill_trust`	Check the supply-chain trust of a ClawHub (OpenClaw) skill BEFORE installing or invoking it. After the Feb-2026 ClawHavoc supply-chain attack, third-party skills can carry malware. Returns a PASS/UNCERTAIN/FAIL badge and 0-100 score aggregating ClawHub's published security scan (VirusTotal + model), moderation verdict, and provenance. Malicious/suspicious/blocked => FAIL; unscanned => UNCERTAIN.
`verify_before_call`	Run a signed pre-invocation verification immediately before an agent sends money, credentials, private data, or write access to an MCP server. The first 3 verifications per agent are free. After that, authenticate the MCP HTTP request with Authorization: Bearer do_<api_key> for Stripe metering ($0.01/call), or call once without payment to receive x402 instructions and retry with payment_tx. Returns PASS/UNCERTAIN/FAIL/UNRATED, evidence freshness, recommendation, and a signed diligence receipt.
`paid_trust_verdict`	Get the PREMIUM behavioral trust verdict for an MCP server, with a signed, citable, tamper-evident attestation receipt. This is a paid x402 service: call WITHOUT payment_tx to receive payment instructions (0.001 USDC on Base), pay, then call again WITH the payment_tx (transaction hash, single-use) to receive the full verdict + receipt. The free check_trust tool remains available for basic scores.
`verify_attestation`	Cryptographically verify a Dominion signed attestation (JWS) — e.g. a trust-verdict receipt, gateway attestation, or MCP Verified badge. Stateless: checks the Ed25519 signature against Dominion's published public key (no trust in this server required). Use this to confirm a receipt another party gave you is authentic and untampered.
`preflight_check`	Run a PRE-FLIGHT due-diligence check on an MCP server BEFORE your agent invokes it. Returns a verdict (PASS/UNCERTAIN/FAIL/UNRATED) plus a SIGNED, timestamped diligence receipt you keep as proof you performed a trust check — the standard of care after the ClawHavoc/Miasma supply-chain attacks. Call this before connecting to or invoking any unfamiliar MCP server.
`report_interaction`	Report the outcome of calling an MCP server. Call this AFTER you use any MCP server to contribute to the trust network. Your report helps other agents make better decisions. This is free and takes <1ms.
`get_leaderboard`	Get the top-rated MCP servers, optionally filtered by category. Use this to discover the most reliable MCP servers in the ecosystem. Categories include: weather, finance, code, data, search, compliance, transport, productivity, communication.
`get_baselines`	Get behavioral baselines for a tool category. Shows what 'normal' looks like — average latency, success rates, typical call patterns. Use this to evaluate whether a specific server's performance is within normal range for its category.
`check_anomaly`	Check if observed behavior from an MCP server is anomalous compared to baselines. Use this when a server seems slow, unreliable, or returns unexpected results. Returns whether the behavior deviates significantly from normal patterns.
`register_server`	Register a new MCP server in the observatory. Server owners can register their servers to start building a trust score. Registration is free.
`get_server_history`	Get daily trust score and performance history for a server over the last 30 days. Use this to see trends — is the server improving or degrading?
`observatory_stats`	Get overall statistics about the Dominion Observatory — total servers tracked, total interactions recorded, coverage by category, and data freshness. Use this to understand the scope of the trust network.
`get_compliance_report`	Export a compliance-ready audit trail of all recorded interactions. Formatted for EU AI Act Article 12 and Singapore IMDA Agentic AI Governance Framework. Filter by server, agent, or date range. Essential for enterprises that need to prove their AI agents are behaving correctly.

Quick Start

For agents (MCP)

Connect to: https://dominionobservatory.com/mcp

For developers (REST API)

# Check trust score
curl "https://dominionobservatory.com/api/trust?url=https://example.workers.dev/mcp"

# View leaderboard
curl "https://dominionobservatory.com/api/leaderboard"

# Network stats
curl "https://dominionobservatory.com/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.

Operator

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

License

MIT

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