Set up sentinel-ai in LangGraph

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Real-time AI safety guardrails for LLM apps. 10 scanners: prompt injection, PII, harmful content, code vulnerabilities, obfuscation detection. Sub-ms latency. Python + TypeScript SDKs. MCP proxy. Claude Code hooks.

01Configuration

# sentinel-ai via LangGraph
# transport: unknown
# launch: the server's install method

LangGraph connects to MCP servers in code. Use its MCP client with the command/URL below; exact API varies by version.

02Steps

Make sure LangGraph is installed and up to date.
Wire the server into LangGraph using its MCP client API.
Provide any required API keys/credentials as environment variables.
Restart LangGraph and confirm sentinel-ai’s tools appear.

03Other runtimes

Claude Desktop Cursor Windsurf Cline Continue Goose VS Code OpenAI Agents SDK CrewAI

04Provenance

config_sourcegenerated from captured install method

last_checked2026-06-29 07:41Z

sourcesGitHub repo search [p4]

Next step

Ship sentinel-ai to your agents as a governed Loadout — config, scopes, and approval rules in one place.

Build a Loadout

See also: server page · is it safe? · alternatives