Guardrly

Created By
fishcoco-code2 months ago
Non-invasive AI Agent operation monitoring — audit every API call your agent makes to Shopify, Meta Ads, and more. Real-time alerts, audit logs, and operation history. Works with Claude Desktop, Cursor, and any MCP-compatible AI tool.
Overview

Guardrly — AI Agent Operation Monitor

Guardrly is a non-invasive MCP Server that monitors every API call your AI Agent makes to external platforms like Shopify and Meta Ads.

Why Guardrly?

AI Agents like Claude Code and Cursor can execute hundreds of API calls autonomously. Without visibility, you risk:

  • Unexpected data modifications (deleted products, cancelled orders)
  • Platform bans from rate limit violations
  • No audit trail when something goes wrong

Key Features

  • Real-time interception — Every HTTP request your Agent makes passes through Guardrly first
  • Automatic PII scrubbing — API keys, tokens, and sensitive data are removed before any data leaves your machine
  • 100+ semantic rules — For Shopify Admin API and Meta Marketing API
  • Risk-based alerts — Email notifications for Level 3 critical operations
  • Complete audit trail — Query every Agent operation from your Dashboard

Supported Platforms

  • Shopify Admin API — 50 rules, 10 operation categories
  • Meta Ads API — 50 rules, 10 operation categories
  • Generic HTTP — Basic logging for any other API

Quick Install

Mac / Linux: ```bash curl -fsSL https://guardrly.com/install.sh | bash ```

Windows (PowerShell): ```powershell irm https://guardrly.com/install.ps1 | iex ```

Pricing

Free tier available. Paid plans start at $49/month.

Server Config

{
  "mcpServers": {
    "guardrly": {
      "command": "guardrly",
      "args": [],
      "env": {
        "GUARDRLY_API_KEY": "your_api_key_here",
        "GUARDRLY_API_URL": "https://api.guardrly.com",
        "HMAC_SECRET": "your_hmac_secret_here"
      }
    }
  }
}
Project Info
Created At
2 months ago
Updated At
2 months ago
Author Name
fishcoco-code
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# govql-mcp-server An MCP (Model Context Protocol) server for [GovQL](https://govql.us) — gives AI clients like Claude Desktop, Claude Code, and Cursor direct access to the US Congressional GraphQL API at [api.govql.us/graphql](https://api.govql.us/graphql) without bespoke HTTP wiring. For the design rationale (why FastMCP-Python, the passthrough+curated philosophy, roadmap through v0.4), see [design.md](https://github.com/govql/govql/blob/main/mcp-server/docs/design.md). ## What you can do with it Ask an agent questions like: - *"How did Vermont's two senators vote on the most recent nomination?"* - *"Which legislators in the 118th Congress switched parties during their service?"* - *"Compare Senator Sanders' voting record to Senator Murkowski's on cloture votes in the most recent Congress."* The agent picks the right tool, writes the GraphQL query against the live schema, and parses the response — no manual API wrangling. ## Install The server runs as a per-client subprocess over stdio. Pick your client: ### Claude Desktop Edit `claude_desktop_config.json` (Settings → Developer → Edit Config): ```json { "mcpServers": { "govql": { "command": "uvx", "args": ["govql-mcp-server"] } } } ``` Restart Claude Desktop. The `govql` tools appear in the tools panel. ### Claude Code Add to `.mcp.json` in your project (or `~/.mcp.json` for global): ```json { "mcpServers": { "govql": { "command": "uvx", "args": ["govql-mcp-server"] } } } ``` ### Cursor Settings → MCP → Add Server. Use the same `command` / `args` as above. ### Other clients Any MCP-compatible client that supports stdio servers will work. The command is `uvx govql-mcp-server` with no required arguments. ## Tools | Tool | Purpose | |---|---| | `execute_graphql` | Run any GraphQL query against the GovQL endpoint. Returns the result plus an `last_ingest` timestamp so the agent can reason about data freshness. | | `list_types` | Returns the names and kinds of every type in the GovQL schema. Optional `kind` filter (`"OBJECT"`, `"INPUT_OBJECT"`, `"ENUM"`, etc.) to narrow further. Start here when you don't know what's queryable. | | `describe_type` | Returns one type's full details — fields, arg signatures, input fields, enum values. Call after `list_types` to learn the shape of a specific type before writing a query. | ## Configuration All env vars are optional — the package is zero-config for end users. | Env var | Default | Purpose | |---|---|---| | `GOVQL_ENDPOINT` | `https://api.govql.us/graphql` | Endpoint to query. Override to point at a local dev stack. | | `GOVQL_TIMEOUT_MS` | `30000` | Per-request HTTP timeout. | | `LOG_LEVEL` | `INFO` | Logging level. Logs go to stderr only (stdout is reserved for the MCP transport). | ## Limits (enforced by the upstream API) - Max query depth: 10 - Max query complexity: ~10 billion points (`first: N` multiplies child cost by N — keep page sizes reasonable on deeply nested queries) - Rate limit: 100 requests / 60 s per source IP A depth or complexity violation surfaces as a GraphQL `errors` entry in the tool response so the agent can adjust and retry. ## Data freshness Every `execute_graphql` response includes a `last_ingest` ISO timestamp. Vote data refreshes hourly; legislator data refreshes daily. ## Status Version 0.1.0 ships three foundational tools: a GraphQL passthrough (`execute_graphql`) and two narrow schema-discovery tools (`list_types`, `describe_type`). Curated higher-level tools (`find_legislator`, `get_voting_record`, `compare_voters`, etc.) are planned for subsequent releases — see [design.md](https://github.com/govql/govql/blob/main/mcp-server/docs/design.md) for the roadmap. ## Links - [GovQL project site](https://govql.us) - [GraphQL API](https://api.govql.us/graphql) - [Source / issues](https://github.com/govql/govql)

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