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Keycloak Identity MCP Server and Agent for Agentic AI!

Project description

Keycloak Agent

MCP Server | Agent

PyPI - Version MCP Server License GitHub

Keycloak Identity and Access Management MCP Server + Agent for the agent-utilities ecosystem. Built with the standardized dynamic-facade architecture, custom API routing, and FastMCP tool registration.

Documentation — Installation, deployment, usage across the API, CLI, and MCP interfaces, and guidance for provisioning the Keycloak platform are maintained in the official documentation.

Table of Contents


Overview

Keycloak MCP provides a high-performance, model-optimized interface to Keycloak capabilities. It isolates the model from underlying API transport complexity, ensuring safe, idempotent, and highly traceable system interactions.


Features

  • Dynamic Facade Orchestration: Integrates multi-inheritance clients cleanly under a single facade.
  • Battle-Tested Resilience: Out-of-the-box credential authentication, connection polling, and request retry strategies.
  • FastMCP Declarative Tools: Fast, native schema registration with full inline validation.
  • Complete Test Intent Diversity: Deep, automated unit, integration, and mock tests ensuring high code coverage.

⚙️ Dynamic Tool Selection & Visibility

This MCP server supports dynamic toolset selection and visibility filtering at runtime. This allows you to restrict the set of exposed tools in order to prevent blowing up the LLM's context window.

You can configure tool filtering via multiple input channels:

  • CLI Arguments: Pass --tools or --toolsets (or their disabled counterparts --disabled-tools and --disabled-toolsets) during startup.
  • Environment Variables: Define standard environment variables:
    • MCP_ENABLED_TOOLS / MCP_DISABLED_TOOLS
    • MCP_ENABLED_TAGS / MCP_DISABLED_TAGS
  • HTTP SSE Request Headers: Pass custom headers during transport initialization:
    • x-mcp-enabled-tools / x-mcp-disabled-tools
    • x-mcp-enabled-tags / x-mcp-disabled-tags
  • HTTP SSE Request Query Parameters: Append query parameters directly to your transport connection URL:
    • ?tools=tool1,tool2
    • ?tags=tag1

When query strings or parameters are supplied, an LLM-free Knowledge Graph resolution layer (using DynamicToolOrchestrator) matches query intents against known tool tags, names, or descriptions, with safe fallback and automated 24-hour background cache refreshing.


Installation

Install in editable mode directly inside your active workspace:

pip install -e .[all]

Or via the uv tool:

uv pip install -e .

Usage

You can launch the FastMCP server in stdio mode via Python module execution:

import asyncio
from keycloak_agent.mcp_server import get_mcp_instance

async def main():
    mcp = get_mcp_instance()
    # Execute stdio loop or launch server
    print("MCP Server ready.")

if __name__ == "__main__":
    asyncio.run(main())

For direct shell launch, execute:

python -m keycloak_agent.mcp_server

Configuration

The package is fully configurable via the environment variables listed below:

Variable Description Default Required
KEYCLOAK_URL Keycloak Base Admin URL http://localhost:8080 Yes
KEYCLOAK_USERNAME Admin account username admin Yes
KEYCLOAK_PASSWORD Admin account password admin_secure_password Yes
KEYCLOAK_REALM KeycloakRealm name master Yes

A local template is supplied inside .env.example. Copy this file as .env and fill out your specific service endpoint parameters before starting execution.


MCP Tools

The following declarative FastMCP tools are registered and available to upstream AI agents:

Tool Name Description Parameters
get_users List realm users limit: int = 100
create_user Create user in realm username: str, email: str, enabled: bool = True
get_realms List realms None
get_clients List realm clients None

See docs/overview.md or docs/concepts.md for deeper operational examples.


Architecture

This package uses the standardized Agent-Utilities dynamic facade architecture:

graph TD
    User([User Agent]) --> Server[FastMCP Server]
    Server --> Facade[Api Dynamic Facade]
    Facade --> ClientBase[ApiClientBase]
    Facade --> Auth[Credentials Auth Handler]
    ClientBase --> Service([External Service API])

Deployment

Bare-Metal (Standard pip)

  1. Set up your Python virtual environment (>= 3.10).
  2. Install the package: pip install .[all]
  3. Export credentials:
    export KEYCLOAK_URL="http://localhost:8080"
    
  4. Run: python -m keycloak_agent.mcp_server

Container (Docker Compose)

A standard compose structure is provided inside the docker/ folder. Build and deploy:

docker compose -f docker/compose.yml up --build -d

Additional Deployment Options

keycloak-agent can also run as a local container (Docker / Podman / uv) or be consumed from a remote deployment. The Deployment guide has full, copy-paste mcp_config.json for all four transports — stdio, streamable-http, local container / uv, and remote URL:

  • Local container / uv — launch the server from mcp_config.json via uvx, docker run, or podman run, or point at a local streamable-http container by url.
  • Remote URL — connect to a server deployed behind Caddy at http://keycloak-mcp.arpa/mcp using the "url" key.

Contributing

Please audit all code changes against ecosystem guidelines in CONTRIBUTING.md if available, and run:

pre-commit run --all-files

Documentation

The complete documentation is published as the official documentation site and is the recommended reference for installation, deployment, and day-to-day operation.

Page Contents
Installation pip, source, extras, prebuilt Docker image
Deployment run the MCP server and agent, Compose, Caddy + Technitium, env config
Usage the MCP tools, the Api client, the CLI
Backing Platform deploy Keycloak with Docker
Overview the dynamic facade and tool surface
Concepts concept registry (CONCEPT:KEY-*)

AGENTS.md is the canonical contributor/agent guidance.

License

This project is licensed under the MIT License. See the LICENSE file for complete details.

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