MCP-Persona - Collaboration Platforms: leaderboard
Metric: Checkpoint accuracy (%): mean LLM-judged score (0, 0.5 or 1) of the sub-task checkpoints in a task, averaged over tasks, single-server collaboration-platform tasks (Lark, Slack, WeCom); 173 human-verified personal-application tasks on 12 simulated MCP servers (Lark, Slack, WeCom, Notion, Obsidian, Rednote, Reddit, Instagram, email and search tools), up to 20 tool-calling rounds, GPT-4o judge; higher is better. Source: arxiv.org. Saturation forecast: Around 2029. 13 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | GPT-5 | 43.5 |
| 2 | Claude Sonnet 4.5 | 39.94 |
| 3 | Claude Opus 4.1 | 38.79 |
| 4 | O4 Mini | 34.38 |
| 5 | O3 | 26.41 |
| 6 | GPT-4o (2024-11-20) | 24.5 |
| 7 | Qwen 3 235B A22B 2507 Instruct | 23.55 |
| 8 | Qwen3 Coder | 23.5 |
| 9 | Gemini 2.5 Pro | 22.58 |
| 10 | DeepSeek V3 (0324) | 19.22 |
| 11 | Grok 4 | 17.8 |
| 12 | Gemini 3 Pro | 14.01 |
Interactive version: theaggregate.ai/benchmark?slug=mcp-persona-collaboration-platforms · How It Works · Data refreshed daily, snapshot 2026-09-29.