MCP Atlas Leaderboard

Multi-server tool orchestration. 36 real MCP servers, 1,000 tasks, claims-based scoring. The benchmark that tests what AI agents actually do — chain tools together correctly.

Last updated: August 14, 2026 · 🆕 Muse Spark 1.2 leads at 90.3%; Claude Opus 5 (85.8%) and Inkling-Small (79.6%) added · SWE-bench Pro → · Terminal-Bench →

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MCP Atlas Score Comparison

Vendor-published scores; hover to inspect the source. Cross-harness results are directional.

About MCP Atlas: 1,000-task benchmark across 36 real MCP servers. Tests multi-step tool orchestration — calling the right API, in the right order, with the right parameters. Scale's April 2026 update replaced a 20-turn limit with a 100 tool-call budget and claims-based scoring.
⚠️ Methodology note: Scores below come from different vendors using their own evaluation scaffolds. Scores from different sources are NOT directly comparable — a 83.6% from Google's harness vs 83.3% from Anthropic's harness doesn't mean one model is definitively better. Within a single lab's table (e.g., Z.AI's cross-model table), scores ARE comparable.
🆕 Muse Spark 1.2 leads at 90.3% in Meta's official evaluation (Muse Code harness) — the highest published vendor score to date. Claude Opus 5 scores 85.8% (Anthropic harness, xhigh), independently mirrored by Scale SEAL at 85.8% ± 2.1. Muse Spark 1.1 (88.1%) remains Meta's previous-generation result, ahead of Gemini 3.5 Flash's 83.6% vendor figure. Kimi K3 scores 84.2% on Moonshot's 500-task public subset with a 100-turn limit and Gemini 3.1 Pro as judge. Because these use different subsets and scaffolds, the ordering is directional rather than a controlled head-to-head.

Test tool orchestration on real MCP servers

20+ LLMs on CodingFleet. Run your own MCP tool chains. Benchmarks are directional — your codebase is the real test.

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