llmboard.aiLeaderboard Center
Overall
Overall RankingOpen Models
Tools
Model DirectoryCompare Models
Capabilities
CodingReasoningMathKnowledgeInstruction Following
Price & Efficiency
Price & ValueCapability vs. PriceRuntime Performance
Modalities
Image GenerationVideo GenerationSpeech ModelsEmbeddings
Core Benchmarks
GPQAMMLU-ProAIME 2025SWE-Bench VerifiedMMLUHumanity's Last ExamLiveCodeBenchMATHHumanEvalMMMU-ProView all benchmarks
Methods
Scoring & Data
393 models668 benchmarks

Leaderboard Center

Overall RankingCodingCore BenchmarksPrice & ValueRuntime Performance

Modalities

All ModelsImage GenerationImage EditingVideo GenerationImage-to-VideoVideo EditingText-to-SpeechSpeech-to-TextEmbeddings

Data & Methods

Scoring MethodAll BenchmarksReasoningMath

Vendors

All VendorsOpenAIAnthropicGoogle
llmboard.aiCopyright 2026 llmboard.ai

agents benchmark

MCP-Mark

MCP-Mark evaluates LLMs on their ability to use Model Context Protocol (MCP) tools effectively, testing tool discovery, selection, invocation, and result interpretation across diverse MCP server scenarios.

Updated Aug 11, 2026

Models8
Model coverage8
MetricScore
EvidenceB

On this page

  • Ranking
  • Distribution
  • Highlights
  • About
  • FAQ

MCP-Mark Ranking

Higher score ranks better on this benchmark.

8 rows
Columns

Show columns

01MAKimi K2.7 CodeMoonshot AI81.1%100.0%8CAug 11, 2026
02ACQwen3.7 MaxAlibaba Cloud / Qwen Team60.8%85.7%8CAug 11, 2026
03ACQwen3.7-PlusAlibaba Cloud / Qwen Team58.7%71.4%8CAug 11, 2026
04MAKimi K2.6Moonshot AI55.9%57.1%8CAug 11, 2026
05ACQwen3.6 PlusAlibaba Cloud / Qwen Team48.2%42.9%8CAug 11, 2026
06ACQwen3.5-397B-A17BAlibaba Cloud / Qwen Team46.1%28.6%8CAug 11, 2026
07DEDeepSeek-V3.2DeepSeek38.0%14.3%8CAug 11, 2026
08ACQwen3.6-35B-A3BAlibaba Cloud / Qwen Team37.0%0.0%8CAug 11, 2026

MCP-Mark Score Distribution

A closer view of the leading scores on this benchmark.

MCP-Mark

MCP-Mark Highlights

The leading models and scores on this benchmark.

Rank #1Kimi K2.7 Code81.1%Rank #2Qwen3.7 Max60.8%Rank #3Qwen3.7-Plus58.7%Rank #4Kimi K2.655.9%

What is MCP-Mark?

What MCP-Mark measures and how its scores work.

MCP-Mark evaluates LLMs on their ability to use Model Context Protocol (MCP) tools effectively, testing tool discovery, selection, invocation, and result interpretation across diverse MCP server scenarios.

Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.

Family
MCP-Mark
Modality
text
Primary category
agents
Score direction
higher
LLMBoard eligible
Yes
Evaluation key
mcp-mark|llm-stats-current

Benchmark scores retain their original unit. Overall score eligibility is shown separately.

FAQ

Common questions about MCP-Mark.

Which model scores highest on MCP-Mark?

Kimi K2.7 Code is currently ranked first with 81.1%.

What does MCP-Mark measure?

MCP-Mark evaluates LLMs on their ability to use Model Context Protocol (MCP) tools effectively, testing tool discovery, selection, invocation, and result interpretation across diverse MCP server scenarios.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

8 model results are currently shown.

Does this benchmark affect the overall score?

Yes. This benchmark can contribute to the current LLMBoard capability score.