by KryptosAI
CI-native security testing for MCP servers. Attack simulation, schema drift detection, and health scoring before agents depend on them.
# Add to your Claude Code skills
git clone https://github.com/KryptosAI/mcp-observatoryGuides for using ai agents skills like mcp-observatory.
Last scanned: 7/3/2026
{
"issues": [],
"status": "PASSED",
"scannedAt": "2026-07-03T07:19:46.952Z",
"npmAuditRan": true,
"pipAuditRan": true,
"promptInjectionRan": true
}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 176 GitHub stars.
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.
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).
mcp-observatory is primarily written in HTML. It is open-source under KryptosAI on GitHub, so you can review or fork the full source.
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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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.
npx @kryptosai/mcp-observatory demo
Scans your configured MCP servers (or a built-in demo server if you have none) and shows your safety grade in seconds. No config, no arguments — instant value.
Have servers? Scan them all:
npx @kryptosai/mcp-observatory
Test a specific server:
npx @kryptosai/mcp-observatory test npx -y @modelcontextprotocol/server-everything
Add CI + Code Scanning in one command:
npx @kryptosai/mcp-observatory setup-ci --all --command "npx -y my-mcp-server" --sarif --schedule weekly
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:
setup-ci --allaudit --profile nsa-mcpallow, gate, rerun, quarantine, or escalateSee GitHub Code Scanning for MCP servers, MCP Receipts, Safety Methodology, MCP Server Safety Index, MCP Observatory Contributors, hosted client contract, repository boundary, open core boundary, and commercial support.
We scan ourselves with mcp-observatory on every release. See results →
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 can use the fixed-scope MCP Release Gate Pilot.
Local OSS use stays free under MIT. Teams running MCP in production can use the MCP Release Gate Pilot for safe-mode evidence, SARIF/Code Scanning setup, CI rollout, private reporting, and owner-ready remediation notes. The fixed public entry offer is $15,000 for 1-3 critical MCP servers over ten business days; broader work is scoped after the release decision.
The open source repo is the portable evidence engine. Hosted authentication, retention, organization workflows, fleet coordination, and private intelligence stay outside the OSS package; see the repository boundary.
Run npx @kryptosai/mcp-observatory cloud, open a pilot request from the issue chooser, or see COMMERCIAL.md. Also see privacy, campaign attribution, and terms for production use.
| Feature | mcp-observatory | Snyk agent-scan | Cisco mcp-scanner | agent-shield |
|---|---|---|---|---|
| MCP-native | ✓ | ✓ | ✓ | ✓ |
| Attack simulation | ✓ | ✗ | ✗ | ✗ |
| Schema drift detection | ✓ | ✗ | ✗ | ✗ |
| Record/replay/verify | ✓ | ✗ | ✗ | ✗ |
| Health scoring (0-100) | ✓ | ✗ | ✗ | ✗ |
| SARIF output | ✓ | ✓ | ✓ | ✓ |
| CI/CD native (setup-ci) | ✓ | ✓ | ✓ | ✓ |
| Public Safety Index | ✓ | ✗ | ✗ | ✗ |
| Runtime enforcement via mcp-seatbelt | ✓ | ✗ | ✗ | ✗ |
Scan every MCP server in your Claude config:
npx @kryptosai/mcp-observatory
Go deeper — also invoke safe tools to verify they actually run:
npx @kryptosai/mcp-observatory scan deep
Test a specific server:
npx @kryptosai/mcp-observatory test npx -y @modelcontextprotocol/server-everything
Add it to Claude Code as an MCP server:
claude mcp add mcp-observatory -- npx -y @kryptosai/mcp-observatory serve
Or add it manually to your config:
{
"mcpServers": {
"mcp-observatory": {
"command": "npx",
"args": ["-y", "@kryptosai/mcp-observatory", "serve"]
}
}
}
| Command | What it does |
|---|---|
scan |
Auto-discover servers, check them, and run safe attack-readiness simulation by default |
scan deep |
Scan, run safe attack simulation, and also invoke safe tools to verify they execute |
test <cmd> / test --target <file> |
Test one server and emit an action receipt by command or target config |
record <cmd> |
Record a server session to a cassette file for offline replay |
replay <cassette> |
Replay a cassette offline — no live server needed |
verify <cassette> <cmd> |
Verify a live server still matches a recorded cassette |
diff <base> <head> |
Compare two run artifacts for regressions and schema drift |
watch <config> |
Watch a server for changes, alert on regressions |
suggest |
Detect your stack and recommend MCP servers from the registry |
serve |
Start as an MCP server for AI agents |
lock |
Snapshot MCP server schemas into a lock file |
lock verify |
Verify live servers match the lock file |
history |
Show health score trends for your MCP servers |
setup-ci / init-ci |
Create a GitHub Action and badge snippet for MCP compatibility/security checks |
setup-ci --sarif |
Generate a workflow that uploads normalized findings to GitHub Code Scanning |
setup-ci --doctor |
Inspect whether the repository has a complete CI adoption kit |
risk-graph --input <path> |
Merge receipts and run artifacts into JSON, Markdown, and HTML MCP risk graphs |
--no-attack-sim |
Opt |