Toolathlon (Tool Decathlon)
Benchmark of 108 long-horizon agent tasks across 32 real applications and 604 tools (mostly MCP servers), each checked by a deterministic evaluation script.
Tags
Description
Tasks start from realistic environment states (e.g. Canvas courses, real spreadsheets, Kubernetes clusters, WooCommerce shops) with deliberately fuzzy instructions, average about 20 tool-calling turns, and often span several apps. Each task runs in its own container. In the ICLR 2026 paper the best model, Claude 4.5 Sonnet, solved 38.6%. The repository is the Toolathlon-Verified final release (June 2026), with trajectories on Hugging Face, a free public evaluation service and a sandboxed branch. The repository has no license file.
Related
- MCPMark: Stress-testing benchmark for agentic models using real MCP environments (Notion, GitHub, Filesystem, Postgres, Playwright), with strict automated verifiers and sandboxed tasks.
- MCP-Universe: Salesforce AI Research benchmark and framework that evaluates LLMs and agents on real-world tasks against live MCP servers, with a public leaderboard.
- MCP-Bench: Accenture's benchmark for tool-using agents on complex real-world tasks across 28 live MCP servers and 250 tools (finance, travel, science, academic search).
- τ-bench (tau2-bench): Sierra's benchmark for tool-agent-user interaction in real-world domains.
- AppWorld: Benchmark and sandbox of 9 simulated day-to-day apps operable via 457 APIs and populated by ~100 simulated people, for evaluating function-calling and interactive coding agents.
Guides & comparisons
- DevOps and observability MCP servers compared (Comparison): Eight official MCP servers for infrastructure and operations work (Kubernetes, Terraform, Buildkite, Azure DevOps, Heroku, Datadog, Grafana and Sentry) compared on what they cover, where they run, how they authenticate and how far their read-only modes actually go.
Sources
Machine-readable
- JSON
- Markdown
- Source file on GitHub (edit via pull request)