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Toolathlon Gym

v1.0.0•Developer Tools•stable

Toolathlon-Gym for testing AI agents real-world tool-use capabilities across diverse MCP servers.

toolathlon-gymmcpai-integration
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What is Toolathlon Gym?

Toolathlon Gym is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to toolathlon-gym for testing ai agents real-world tool-use capabilities across diverse mcp servers.

Toolathlon-Gym for testing AI agents real-world tool-use capabilities across diverse MCP servers.

This server falls under the Developer Tools category on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

  • Toolathlon-Gym for testing AI agents real-world tool-use cap

Use Cases

Test AI agent tool-use capabilities across diverse MCP servers.
Benchmark real-world agent performance and integration quality.
eigent-ai

Maintainer

LicenseApache-2.0
Languagepython
Versionv1.0.0
UpdatedMay 21, 2026
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux
View SourceBrowse All Servers

Installation

Manual Installation

npx toolathlon-gym

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

How to Set Up and Use Toolathlon Gym

Toolathlon-Gym is a benchmarking framework that evaluates AI agents on real-world tool-use tasks across 25 diverse MCP servers, including PostgreSQL, Google Calendar, Notion, Playwright, and financial data sources. It spins up a fully containerized environment with Docker Compose so every benchmark run is reproducible and isolated. Developers building or evaluating agent systems use it to measure how reliably their chosen model navigates multi-step tasks that cross service boundaries.

Prerequisites

  • Docker and Docker Compose installed on your machine
  • A supported model API key (Anthropic, OpenAI, Gemini, or compatible endpoint)
  • Sufficient disk space for the PostgreSQL data image (~500 MB)
  • An MCP-compatible client or the bundled agent runner scripts
  • Git to clone the repository
1

Clone the repository

Pull down the Toolathlon-Gym source code which contains the Docker configuration, task definitions, and agent runner scripts.

git clone https://github.com/eigent-ai/toolathlon_gym.git
cd toolathlon_gym
2

Build the agent Docker image

Navigate to the Toolathlon_Pack directory and build the image that packages all 25 MCP servers alongside their dependencies.

cd Toolathlon_Pack
docker build -t toolathlon-pack:latest .
3

Start the PostgreSQL database

Launch the Postgres container. On first start it auto-initializes from the bundled db/init.sql.gz, pre-loading all benchmark datasets (Canvas LMS, WooCommerce, Yahoo Finance snapshots, etc.).

docker compose up -d postgres
4

Verify the setup

Run the sanity-check script to confirm the database initialized correctly and all services are reachable before running benchmark tasks.

bash scripts/test_containerized.sh
5

Run a single benchmark task

Execute one task against your chosen model. Set MODEL_PLATFORM to openai_compatible, openai, anthropic, or gemini. MAX_STEPS controls the per-task step budget (default 100).

MODEL_PLATFORM=anthropic \
MODEL_NAME=claude-sonnet-4-5 \
MODEL_API_KEY=sk-ant-xxx \
bash scripts/run_containerized.sh howtocook-meal-plan-gcal 60
6

Run the full parallel benchmark suite

Evaluate all tasks in parallel (10 concurrent workers) to get aggregate performance scores. Results and full LLM trajectories are saved under dumps/<task>/<timestamp>/.

MODEL_PLATFORM=anthropic \
MODEL_NAME=claude-sonnet-4-5 \
MODEL_API_KEY=sk-ant-xxx \
IMAGE=toolathlon-pack:latest \
bash run_parallel.sh 10

Toolathlon Gym Examples

Client configuration

Toolathlon-Gym is primarily run via its bundled scripts rather than a standalone MCP config block. The environment variables below are the canonical way to point it at your model provider.

{
  "mcpServers": {
    "toolathlon-gym": {
      "command": "bash",
      "args": ["scripts/run_containerized.sh", "<task-name>", "60"],
      "env": {
        "MODEL_PLATFORM": "anthropic",
        "MODEL_NAME": "claude-sonnet-4-5",
        "MODEL_API_KEY": "sk-ant-xxx",
        "IMAGE": "toolathlon-pack:latest",
        "MAX_STEPS": "100"
      }
    }
  }
}

Prompts to try

These prompts map to real benchmark tasks that exercise different MCP servers in the Gym environment.

- "Plan a week of meals from the HowToCook dataset and add them to Google Calendar"
- "Query the WooCommerce orders database and summarize revenue by category for last month"
- "Search Yahoo Finance for the top 5 S&P 500 movers today and save a summary to Notion"
- "Use Playwright to fill out the registration form at the demo e-commerce site"
- "Generate a PDF report from the employee table in the PostgreSQL database"

Troubleshooting Toolathlon Gym

PostgreSQL container fails to start or reports 'database system identifier differs'

Remove the old Postgres volume with 'docker compose down -v' and restart. The volume is incompatible after a rebuild of the init.sql.gz data.

Model API calls return authentication errors during task runs

Ensure MODEL_API_KEY is exported in your shell or prefixed on the command line. For Anthropic models set MODEL_PLATFORM=anthropic; for OpenAI-compatible endpoints also set MODEL_API_URL.

Tasks exceed MAX_STEPS and produce incomplete results

Increase MAX_STEPS (e.g. to 150) for complex multi-hop tasks. Check dumps/<task>/<timestamp>/trajectory.json to identify where the agent is looping and tune the system prompt accordingly.

Frequently Asked Questions about Toolathlon Gym

What is Toolathlon Gym?

Toolathlon Gym is a Model Context Protocol (MCP) server that toolathlon-gym for testing ai agents real-world tool-use capabilities across diverse mcp servers. It connects AI assistants to external tools and data sources through a standardized interface.

How do I install Toolathlon Gym?

Follow the installation instructions on the Toolathlon Gym GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.

Which AI clients work with Toolathlon Gym?

Toolathlon Gym works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is Toolathlon Gym free to use?

Yes, Toolathlon Gym is open source and available under the Apache-2.0 license. You can use it freely in both personal and commercial projects.

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Quick Config Preview

{ "mcpServers": { "toolathlon-gym": { "command": "npx", "args": ["-y", "toolathlon-gym"] } } }

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

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