This is an audit layer that sits between Claude and your production APIs like Shopify and Meta Ads, logging every call the agent makes with context about what happened and why. Instead of discovering after the fact that your agent burned through ad budget or modified product listings, you get a readable trail of operations and can set up alerts before destructive actions go through. The compliance angle is interesting too: PII gets scrubbed locally before logs hit their cloud, and you can generate structured evidence if an automated action gets your account flagged. Reach for this when you're running agents with write access to business critical platforms and need to sleep at night.
mcp-name: io.github.fishcoco-code/guardrly-mcp
Website: guardrly.com
Guardrly is a non-invasive AI Agent operation monitoring layer that intercepts, records, and alerts on every API call an AI Agent makes to external platforms - giving users full visibility into what their Agent did, when, and why.
# Mac / Linux
curl -fsSL https://guardrly.com/install.sh | bash
# Windows (PowerShell)
iwr https://guardrly.com/install.ps1 | iex
# Install dependencies
poetry install
# Copy environment template
cp .env.example .env
# Edit .env with your credentials
# Run API server
poetry run uvicorn api.main:app --reload
MIT License. See LICENSE for details.
GUARDRLY_API_KEY*secretYour Guardrly API key from app.guardrly.com/settings
GUARDRLY_API_URLdefault: https://api.guardrly.comGuardrly API endpoint
HMAC_SECRET*secretYour HMAC secret from app.guardrly.com/settings MCP Configuration panel
io.github.ericm1018/skillfm-llm-cost-optimizer-openai-anthropic-usage
io.github.mikerawsonnz/llm-orchestration-agent
io.github.mikerawsonnz/authenticated-llm-agent
labforgedev/copilot-memory-mcp
csoai-org/agent-prompt-injection-firewall-mcp
io.github.mikerawsonnz/authenticated-multi-llm-agent