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Agent package for communicating with LeanIX Enterprise Architecture Management via REST APIs and GraphQL.

Project description

LeanIX Agent - A2A | AG-UI | MCP

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Version: 0.2.0

Overview

LeanIX Agent MCP Server + A2A Agent

Agent package for communicating with LeanIX Enterprise Architecture Management via REST APIs and GraphQL.

This repository is actively maintained - Contributions are welcome!

Features

Core Capabilities

  • FactSheet Management: Create, read, update FactSheets (Applications, Components, etc.)
  • GraphQL Queries: Execute flexible GraphQL queries with variables and operations
  • Metrics & KPIs: Access custom metrics, KPIs, and performance data
  • Discovery Integration: SaaS, SAP, and AI agent discovery services
  • Architecture Relations: Query FactSheet relationships and hierarchies
  • User & Workspace Management: Manage users, permissions, and workspace settings
  • Authentication: Automatic OAuth token management and session handling

API Coverage

The agent provides access to 30+ LeanIX API services with 500+ methods:

  • Pathfinder API: FactSheet operations, relations, and resource models
  • Metrics API: Schema management, KPI tracking, and data points
  • MTM API: Account management, workspace administration, and OAuth
  • Discovery APIs: SaaS, SAP, and AI agent discovery
  • Integration APIs: Collibra, ServiceNow, and Signavio connectors
  • Support APIs: Documents, impacts, navigation, polls, and webhooks

MCP

Using as an MCP Server

The MCP Server can be run in two modes: stdio (for local testing) or http (for networked access).

Environment Variables

  • LEANIX_WORKSPACE: The URL of the target service.
  • LEANIX_API_TOKEN: The API token or access token.

Run in stdio mode (default):

export LEANIX_WORKSPACE="http://localhost:8080"
export LEANIX_API_TOKEN="your_token"
leanix-mcp --transport "stdio"

Run in HTTP mode:

export LEANIX_WORKSPACE="http://localhost:8080"
export LEANIX_API_TOKEN="your_token"
leanix-mcp --transport "http" --host "0.0.0.0" --port "8000"

A2A Agent

Run A2A Server

export LEANIX_WORKSPACE="http://localhost:8080"
export LEANIX_API_TOKEN="your_token"
leanix-agent --provider openai --model-id gpt-4o --api-key sk-...

Docker

Build

docker build -t leanix-agent .

Run MCP Server

docker run -d \
  --name leanix-agent \
  -p 8000:8000 \
  -e TRANSPORT=http \
  -e LEANIX_WORKSPACE="http://your-service:8080" \
  -e LEANIX_API_TOKEN="your_token" \
  knucklessg1/leanix-agent:latest

Deploy with Docker Compose

services:
  leanix-agent:
    image: knucklessg1/leanix-agent:latest
    environment:
      - HOST=0.0.0.0
      - PORT=8000
      - TRANSPORT=http
      - LEANIX_WORKSPACE=http://your-service:8080
      - LEANIX_API_TOKEN=your_token
    ports:
      - 8000:8000

Configure mcp.json for AI Integration (e.g. Claude Desktop)

{
  "mcpServers": {
    "leanix": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "leanix-agent",
        "leanix-mcp"
      ],
      "env": {
        "LEANIX_WORKSPACE": "http://your-service:8080",
        "LEANIX_API_TOKEN": "your_token"
      }
    }
  }
}

Install Python Package

python -m pip install leanix-agent
uv pip install leanix-agent

Repository Owners

GitHub followers GitHub User's stars

Graph Architecture

This agent uses pydantic-graph orchestration for intelligent routing and optimal context management.

---
title: LeanIX Agent Graph Agent
---
stateDiagram-v2
  [*] --> RouterNode: User Query
  RouterNode --> DomainNode: Classified Domain
  RouterNode --> [*]: Low confidence / Error
  DomainNode --> [*]: Domain Result
  • RouterNode: A fast, lightweight LLM (e.g., nvidia/nemotron-3-super) that classifies the user's query into one of the specialized domains.
  • DomainNode: The executor node. For the selected domain, it dynamically sets environment variables to temporarily enable ONLY the tools relevant to that domain, creating a highly focused sub-agent (e.g., gpt-4o) to complete the request. This preserves LLM context and prevents tool hallucination.

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