wger-agent 0.11.1

Wger Workout Manager — exercise database, workout routines, nutrition plans, body measurements, and progress tracking.

Wger - A2A | AG-UI | MCP

Version: 0.11.1

Overview

Wger MCP Server + A2A Agent

Wger Workout Manager — exercise database, workout routines, nutrition plans, body measurements, and progress tracking.

This repository is actively maintained - Contributions are welcome!

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

• WGER_INSTANCE: The URL of the target service.
• WGER_ACCESS_TOKEN: The API token or access token.

Run in stdio mode (default):

export WGER_INSTANCE="http://localhost:8080"
export WGER_ACCESS_TOKEN="your_token"
wger-mcp --transport "stdio"

Run in HTTP mode:

export WGER_INSTANCE="http://localhost:8080"
export WGER_ACCESS_TOKEN="your_token"
wger-mcp --transport "http" --host "0.0.0.0" --port "8000"

A2A Agent

Run A2A Server

export WGER_INSTANCE="http://localhost:8080"
export WGER_ACCESS_TOKEN="your_token"
wger-agent --provider openai --model-id gpt-4o --api-key sk-...

Security & Governance

This project is built on agent-utilities, inheriting enterprise-grade security and governance features.

Authentication & Authorization

Feature	Description
OIDC Token Delegation	RFC 8693 token exchange for user-context propagation from A2A → MCP
Eunomia Policies	Fine-grained, policy-driven tool authorization (none, embedded, remote)
Scoped Credentials	Tools execute with the caller's scoped identity where possible
3LO / OAuth / API Token	Multiple auth strategies with graceful fallback

Eunomia Policy Enforcement

Eunomia provides a policy enforcement point for all tool calls:

• Embedded mode: Load local mcp_policies.json for role-based access, sensitivity gating, and audit logging
• Remote mode: Forward authorization decisions to a central Eunomia policy server for multi-agent governance
• Enable via CLI: --eunomia-type embedded --eunomia-policy-file mcp_policies.json

Runtime Protections

Protection	Description
Tool Guard	Sensitivity detection with human-in-the-loop approval gating
Prompt Injection Defense	Input scanning and repetition/loop guards
Content Filtering	Output schema enforcement and cost budget controls
Stuck Loop Detection	Automatic detection and recovery from agent loops
Context Limit Warnings	Proactive alerts before context window exhaustion

Graph Agent Architecture

The A2A agent uses pydantic-graph orchestration with:

• RouterNode: Lightweight classifier that routes queries to specialized domains
• DomainNode: Focused executor with only relevant tools loaded, preventing tool hallucination
• Approval Gates: Policy-driven approval workflows before sensitive operations
• Usage Guards: Budget and rate limiting enforcement

Production Recommendation: Enable --eunomia-type embedded (or remote) + OIDC delegation + containerized deployment. See agent-utilities documentation for full policy configuration.

Docker

Build

docker build -t wger-agent .

Run MCP Server

docker run -d \
  --name wger-agent \
  -p 8000:8000 \
  -e TRANSPORT=http \
  -e WGER_INSTANCE="http://your-service:8080" \
  -e WGER_ACCESS_TOKEN="your_token" \
  knucklessg1/wger-agent:latest

Deploy with Docker Compose

services:
  wger-agent:
    image: knucklessg1/wger-agent:latest
    environment:
      - HOST=0.0.0.0
      - PORT=8000
      - TRANSPORT=http
      - WGER_INSTANCE=http://your-service:8080
      - WGER_ACCESS_TOKEN=your_token
    ports:
      - 8000:8000

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

{
  "mcpServers": {
    "wger": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "wger-agent",
        "wger-mcp"
      ],
      "env": {
        "WGER_INSTANCE": "http://your-service:8080",
        "WGER_ACCESS_TOKEN": "your_token"
      }
    }
  }
}

Install Python Package

python -m pip install wger-agent

uv pip install wger-agent

Repository Owners

Graph Architecture

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

---
title: Wger 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.

MCP Configuration Examples

stdio (recommended for local development)

{
  "mcpServers": {
    "wger": {
      "command": ".venv/bin/wger-mcp",
      "args": [],
      "env": {
        "WGER_INSTANCE": "",
        "WGER_ACCESS_TOKEN": ""
}
    }
  }
}

Streamable HTTP (recommended for production)

{
  "mcpServers": {
    "wger": {
      "url": "http://localhost:8080/wger-mcp/mcp"
    }
  }
}

Available MCP Tools

This server utilizes dynamic Action-Routed tools to optimize token overhead and maximize IDE compatibility.

Tool Name	Description
wger_body	Consolidated Action-Routed tool for Body. Methods: get_weight_entries, log_body_weight, delete_weight_entry, get_measurements, log_measurement, get_measurement_categories, create_measurement_category, get_gallery
wger_exercise	Consolidated Action-Routed tool for Exercise. Methods: get_exercises, get_exercise_info, search_exercises, get_exercise_categories, get_equipment, get_muscles, get_exercise_images, get_variations
wger_nutrition	Consolidated Action-Routed tool for Nutrition. Methods: get_nutrition_plans, get_nutrition_plan_info, create_nutrition_plan, delete_nutrition_plan, create_meal, create_meal_item, get_ingredients, get_ingredient_info, get_nutrition_diary, log_nutrition
wger_routine	Consolidated Action-Routed tool for Routine. Methods: get_routines, get_routine, create_routine, delete_routine, get_days, create_day, delete_day, get_slots, create_slot, create_slot_entry, get_templates, get_public_templates
wger_routineconfig	Consolidated Action-Routed tool for RoutineConfig. Methods: create_weight_config, get_weight_configs, create_repetitions_config, get_repetitions_configs, create_sets_config, create_rest_config, create_rir_config
wger_user	Consolidated Action-Routed tool for User. Methods: get_user_profile, get_user_statistics, get_user_trophies, get_languages, get_repetition_units, get_weight_unit_settings
wger_workout	Consolidated Action-Routed tool for Workout. Methods: get_workout_sessions, get_workout_session, create_workout_session, delete_workout_session, get_workout_logs, create_workout_log, delete_workout_log