Skip to main content
Glama
guardentryai

GuardEntry MCP Server

Official
by guardentryai
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

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

npm run start:http

CrewAI, LangChain, any HTTP MCP client

stdio

npm start

Claude Desktop, Cursor, VS Code Cline

Related MCP server: SentinelGate

Quick start

git clone https://github.com/guardentryai/mcp-server.git
cd mcp-server
npm install

Create 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 allowlist

Get 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/health

stdio mode (Claude Desktop, Cursor)

npm start

Claude 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

guardentry_evaluate_action

Evaluate a proposed action — returns allow, block, or require_approval with reasoning

guardentry_chat

Natural language interface to GuardEntry

guardentry_list_risks

Query the risk register

guardentry_compliance_status

Get framework readiness (SOC 2, ISO 27001, NIST CSF…)

guardentry_invoke_agent

Run a GuardEntry agent by ID or type

guardentry_invoke_skill

Call a single agent skill directly

guardentry_list_skills

List available skills

guardentry_get_agent_policy

Get the effective policy for an agent

guardentry_confirm_policy

Promote an inferred policy to confirmed

guardentry_update_policy

Update policy rules (blocked actions, allowed tools, approval patterns)

guardentry_list_pending

List actions awaiting dashboard approval

guardentry_action_status

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:http

CrewAI 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.py

Environment variables

Variable

Default

Description

GUARDENTRY_API_KEY

(required)

API key from GuardEntry dashboard

GUARDENTRY_BASE_URL

https://app.guardentry.ai

Override for local/staging

MCP_PORT

3001

HTTP server port

MCP_TOOLS

(all tools)

Comma-separated tool allowlist

License

MIT — see LICENSE

Links

This server cannot be installed

A
license - permissive license
-
quality - not tested
C
maintenance

How are these scores calculated?

Maintenance

–Maintainers
–Response time
–Release cycle
–Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/guardentryai/mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server