# MCP Atlas

> Evaluates how well language models handle real-world tool use through MCP

- Category: [Benchmarks & Leaderboards](https://ailandscape.org/category/benchmarks-leaderboards) › Agent & General Benchmarks
- Homepage: https://scale.com/leaderboard/mcp_atlas
- Added to the landscape: 2026-03-18

## Similar tools in Agent & General Benchmarks

- [APEX-Agents](https://ailandscape.org/tool/apex-agents): Measures whether frontier AI agents can execute real long-horizon tasks
- [ARC-AGI-2](https://ailandscape.org/tool/arc-agi-2): Stress-tests efficiency and capability of state-of-the-art AI reasoning systems
- [Context-Bench](https://ailandscape.org/tool/context-bench): A benchmark for agentic context engineering
- [Modu Merge Rate Leaderboard](https://ailandscape.org/tool/modu-merge-rate-leaderboard): Ranking top coding agents by real-world pull request merge success rates
- [OSWorld](https://ailandscape.org/tool/osworld): Benchmarks multimodal agents on open-ended tasks in real computer environments
- [PR Arena](https://ailandscape.org/tool/pr-arena): Software engineering agents head-to-head on real pull request tasks
- [Repo Bench](https://ailandscape.org/tool/repo-bench): Measures large-context reasoning, edit precision, and instruction adherence
- [Terminal-Bench](https://ailandscape.org/tool/terminal-bench): Benchmark measuring AI agent capabilities in a terminal environment (v1)

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Part of [AI Landscape](https://ailandscape.org), an open map of the AI ecosystem. Web page: https://ailandscape.org/tool/mcp-atlas · Index for AI assistants: https://ailandscape.org/llms.txt