MCP Atlas

MCP Atlas is a benchmark for evaluating AI models on scaled tool use capabilities, measuring how well models can coordinate and utilize multiple tools across complex multi-step tasks.

Claude Opus 4.7 from Anthropic currently leads the MCP Atlas leaderboard with a score of 0.773 across 17 evaluated AI models.

AnthropicClaude Opus 4.7 leads with 77.3%, followed by OpenAIGPT-5.5 at 75.3% and Alibaba Cloud / Qwen TeamQwen3.6 Plus at 74.1%.

Progress Over Time

Interactive timeline showing model performance evolution on MCP Atlas

State-of-the-art frontier
Open
Proprietary

MCP Atlas Leaderboard

17 models
ContextCostLicense
11.0M$5.00 / $25.00
2
OpenAI
OpenAI
1.1M$5.00 / $30.00
3
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
1.0M$0.50 / $3.00
41.6T1.0M$1.74 / $3.48
5
Zhipu AI
Zhipu AI
754B200K$1.40 / $4.40
61.0M$2.50 / $15.00
7284B1.0M$0.14 / $0.28
8
Zhipu AI
Zhipu AI
744B200K$1.00 / $3.20
9
OpenAI
OpenAI
1.0M$2.50 / $15.00
10
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
35B
111.0M$5.00 / $25.00
12200K$5.00 / $25.00
13200K$3.00 / $15.00
14
OpenAI
OpenAI
400K$1.75 / $14.00
15400K$0.75 / $4.50
161.0M$0.50 / $3.00
17400K$0.20 / $1.25
Notice missing or incorrect data?

FAQ

Common questions about MCP Atlas.

What is the MCP Atlas benchmark?

MCP Atlas is a benchmark for evaluating AI models on scaled tool use capabilities, measuring how well models can coordinate and utilize multiple tools across complex multi-step tasks.

What is the MCP Atlas leaderboard?

The MCP Atlas leaderboard ranks 17 AI models based on their performance on this benchmark. Currently, Claude Opus 4.7 by Anthropic leads with a score of 0.773. The average score across all models is 0.662.

What is the highest MCP Atlas score?

The highest MCP Atlas score is 0.773, achieved by Claude Opus 4.7 from Anthropic.

How many models are evaluated on MCP Atlas?

17 models have been evaluated on the MCP Atlas benchmark, with 0 verified results and 17 self-reported results.

What categories does MCP Atlas cover?

MCP Atlas is categorized under reasoning, tool calling, agents, and code. The benchmark evaluates text models.

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