GuardEntry MCP Server
OfficialClick on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@GuardEntry MCP ServerEvaluate: update user role to admin"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
GuardEntry MCP Server
Model Context Protocol (MCP) server for GuardEntry — exposes the Agent Policy Router (APR) as MCP tools so any MCP-compatible AI agent can gate its actions through your compliance policy before executing them.
Transports
Transport | Entry point | Use with |
Streamable HTTP |
| CrewAI, LangChain, any HTTP MCP client |
stdio |
| Claude Desktop, Cursor, VS Code Cline |
Related MCP server: mcp-boundary
Quick start
git clone https://github.com/guardentryai/mcp-server.git
cd mcp-server
npm installCreate a .env file (copy from .env.example):
GUARDENTRY_API_KEY=ge_k1_your_key_here
# GUARDENTRY_BASE_URL=https://app.guardentry.ai # default
# MCP_PORT=3001 # default (HTTP mode only)
# MCP_TOOLS=guardentry_evaluate_action # optional tool allowlistGet an API key at app.guardentry.ai → Settings → API Keys.
HTTP mode (CrewAI, LangChain, etc.)
npm run start:http
# GuardEntry APR MCP server listening on http://localhost:3001/mcp
# Health: http://localhost:3001/healthstdio mode (Claude Desktop, Cursor)
npm startClaude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"guardentry": {
"command": "npx",
"args": ["--yes", "guardentry-mcp"],
"env": { "GUARDENTRY_API_KEY": "ge_k1_your_key_here" }
}
}
}Available tools
Tool | Description |
| Evaluate a proposed action — returns |
| Natural language interface to GuardEntry |
| Query the risk register |
| Get framework readiness (SOC 2, ISO 27001, NIST CSF…) |
| Run a GuardEntry agent by ID or type |
| Call a single agent skill directly |
| List available skills |
| Get the effective policy for an agent |
| Promote an inferred policy to confirmed |
| Update policy rules (blocked actions, allowed tools, approval patterns) |
| List actions awaiting dashboard approval |
| Check the status of a specific action |
Limiting tools (recommended for CrewAI + Claude)
Anthropic's API has a ~16-parameter union-type limit across all active tools. Use MCP_TOOLS to expose only what you need:
MCP_TOOLS=guardentry_evaluate_action npm run start:httpCrewAI integration
from crewai import Agent, Task, Crew, LLM
from crewai.mcp.config import MCPServerHTTP
import os
mcp = MCPServerHTTP(
url="http://localhost:3001/mcp",
headers={"Authorization": f"Bearer {os.environ['GUARDENTRY_API_KEY']}"},
)
agent = Agent(
role="Compliance Analyst",
goal="Gate every action through GuardEntry APR before executing",
backstory="You check compliance policy before any sensitive operation.",
mcps=[mcp],
llm=LLM(model="anthropic/claude-haiku-4-5-20251001",
api_key=os.environ["ANTHROPIC_API_KEY"]),
)Run the smoke test:
GUARDENTRY_API_KEY=ge_k1_... ANTHROPIC_API_KEY=sk-ant-... python test-crewai.pyEnvironment variables
Variable | Default | Description |
| (required) | API key from GuardEntry dashboard |
|
| Override for local/staging |
|
| HTTP server port |
| (all tools) | Comma-separated tool allowlist |
License
MIT — see LICENSE
Links
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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