mcp-observatory

Name: mcp-observatory
Author: KryptosAI

Verified

CI-native security testing for MCP servers. Attack simulation, schema drift detection, and health scoring before agents depend on them.

140stars

15forks

TypeScript

Installation

# Add to your Claude Code skills
git clone https://github.com/KryptosAI/mcp-observatory

Getting Started

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Security ReportVerified

Last scanned: 7/3/2026

{
  "issues": [],
  "status": "PASSED",
  "scannedAt": "2026-07-03T07:19:46.952Z",
  "npmAuditRan": true,
  "pipAuditRan": true,
  "promptInjectionRan": true
}

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README.md

Frequently Asked Questions

What is mcp-observatory?

mcp-observatory is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by KryptosAI. CI-native security testing for MCP servers. Attack simulation, schema drift detection, and health scoring before agents depend on them. It has 140 GitHub stars.

Is mcp-observatory safe to use?

Yes. mcp-observatory passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install mcp-observatory?

Clone the repository with "git clone https://github.com/KryptosAI/mcp-observatory" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is mcp-observatory written in?

mcp-observatory is primarily written in TypeScript. It is open-source under KryptosAI on GitHub, so you can review or fork the full source.

Are there alternatives to mcp-observatory?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh mcp-observatory against similar tools.

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Related Skills

ECC

by affaan-m

The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.

270,372

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Secure the MCP servers you're building. MCP Observatory is the CI-native security tool for teams shipping custom MCP servers. Test during development, catch schema drift, simulate attacks, and generate compliance evidence — before agents depend on your servers.

Also available in Simplified Chinese.

Runtime enforcement: Use mcp-seatbelt to block dangerous MCP tool calls at runtime based on observatory scan results.

Get Started

Step-by-step setup guide · macOS, Windows, Linux · Node.js 20+ and npm (install Node.js LTS).

1. Run your first scan

Open Terminal or PowerShell in your project folder and paste:

npx -y @kryptosai/mcp-observatory@latest

This downloads Observatory and checks your first configured MCP server. With no configured server, it uses an included example. To try only that example, run npx -y @kryptosai/mcp-observatory@latest demo --example.

2. Read the result

The terminal shows the target, grade, findings, and saved receipt path. Failed checks are findings to review, not a request to pay. If connection failed, fix the startup command or credentials and rerun. A demo grade describes the example, not your own server.

3. Save one hosted snapshot free (optional)

In the same project folder, run:

npx -y @kryptosai/mcp-observatory@latest cloud upload

Open the verification link printed in the terminal, confirm the code, connect with GitHub, then return to the terminal. Wait for Upload complete and open the dashboard link. No separate account setup or payment method is needed. Free includes one target, the latest snapshot, seven-day retention, and ten uploads per month.

Local scans and local CI stay free. Individual Pro is $29/month when you need 10 targets, 90-day history, hosted CI ingestion, or hosted HTTP scans.

MCP Observatory uses jurisdiction-aware product telemetry after showing the collection notice. Review the exact fields with telemetry preview, check the current policy with telemetry status, or stop collection at any time with telemetry disable, MCP_OBSERVATORY_TELEMETRY=0, or DO_NOT_TRACK=1. See the complete privacy and telemetry notice.

npx -y @kryptosai/mcp-observatory@latest test npx -y @modelcontextprotocol/server-everything

- uses: KryptosAI/mcp-observatory/action@v1

If this repo is an MCP package, that tests npx -y <package.json name>. Otherwise set command:.

Or generate a full workflow: npx -y @kryptosai/mcp-observatory@latest setup-ci --all --command "npx -y my-mcp-server" --sarif

Install: npx -y @kryptosai/mcp-observatory@latest · brew tap kryptosai/mcp-observatory https://github.com/KryptosAI/mcp-observatory && brew install mcp-observatory · docker pull ghcr.io/kryptosai/mcp-observatory:latest · curl -fsSL https://raw.githubusercontent.com/KryptosAI/mcp-observatory/main/scripts/install.sh | sh

docker run --rm ghcr.io/kryptosai/mcp-observatory:latest demo
docker run --rm ghcr.io/kryptosai/mcp-observatory:latest test npx -y @modelcontextprotocol/server-everything

Scanning a server on the host needs network and, for local files, a volume mount (-v "$PWD:$PWD" -w "$PWD").

Agents: npx -y @kryptosai/mcp-observatory@latest serve

Default-deny connect: npx -y @kryptosai/mcp-observatory@latest protect rewrites every discovered client config (Cursor, Claude, VS Code, .mcp.json, …). Undo: protect --undo. HTTP/SSE servers are left alone.

Runtime deny-default: npx -y @kryptosai/mcp-observatory@latest enforce --start-proxy writes a Seatbelt policy from the scan and starts the proxy. Local scan stays free.

Proof: Safety Index. Upload one hosted snapshot free with cloud upload; Individual Pro is $29/month when you need retained history and hosted CI ingestion.

Learn from production usage

Connect real tool calls to user intent with the usage-learning SDK and CLI: sanitized invocation evidence, opted-in “asked / expected / got” reports, selected conversation excerpts, one-click dissatisfaction flags, intent grouping across captured requests, and regression-case export. Run mcp-observatory usage review --dir private-usage to inspect linked evidence in a loopback-only browser screen. Server logs cannot reveal unshared conversations; observed execution and inferred breakdown signals stay separate. Collection is local and requires explicit integration.

Why MCP Observatory

MCP servers are becoming production dependencies. If agents rely on them, teams need a way to catch broken tools, unsafe schemas, schema drift, slow responses, and security footguns before those failures reach users.

Observatory gives maintainers and teams:

One-command CI setup with setup-ci --all
Profile-mapped audits with audit --profile nsa-mcp
MCP receipts that package target, evidence, verdict, action, and reproduction commands
MCP risk graphs that group servers by capability boundary, receipt state, CI posture, and recommended action
Action receipts that say allow, gate, rerun, quarantine, or escalate
GitHub PR comments for compatibility, drift, and security findings
GitHub Code Scanning SARIF for normalized MCP findings
Health score badges for public trust signals
Record/replay/verify workflows for regression testing
MCP server mode so agents can inspect other MCP servers directly
Production support path for one-user hosted history, CI ingestion, and owner-ready Release Gate remediation

See GitHub Code Scanning for MCP servers, MCP Receipts, Troubleshooting, Safety Methodology, MCP Server Safety Index, MCP Observatory Contributors, hosted client contract, repository boundary, open core boundary, and commercial support.

Self-Assessment

We scan ourselves with mcp-observatory on every release. See results →

For Security And Platform Teams

MCP servers are becoming part of the AI software supply chain. Agents need reliable, testable, auditable tools before those tools become dependencies in mission-critical workflows.

Whether you're shipping one MCP server or running a fleet, MCP Observatory gives you CI-native security scoring, attack simulation, schema drift detection, SARIF/HTML/Markdown reports, and GitHub Code Scanning — from your first npx command to production deployment. Local development stays free; teams with a near-term production approval decision c