reasoning benchmark
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.
Updated Aug 7, 2026
Published models30
Registry coverage30
MetricScore
EvidenceB
MCP Atlas leaderboard
Sorted by the source-provided rank. Higher score is better according to the registry.
Score distribution
Top published rows on the benchmark's original scale.
MCP Atlas highlights
The top published results on this benchmark's own scale.
What is MCP Atlas?
Definition and scoring fields from the benchmark registry.
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.
Scores are shown in ratio. The current registry marks this benchmark as not independently verified with evidence level B.
- Family
- MCP Atlas
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- mcp-atlas|llm-stats-current
Source-native results are preserved. Eligibility for the overall LLMBoard score is a separate policy decision.
FAQ
Common questions about MCP Atlas.
Which model scores highest on MCP Atlas?
Muse Spark 1.1 is currently ranked first with 88.1%.
What does MCP Atlas measure?
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.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
30 unique published model results are currently shown.
Does this benchmark affect the overall score?
This benchmark is marked as eligible for the current LLMBoard capability methodology.