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# Paper: DynamicMCPBench: A Trace-Grounded, Effect-Scored Benchmark for LLM Agents over Live MCP Servers
---
type: paper
title: "DynamicMCPBench: A Trace-Grounded, Effect-Scored Benchmark for LLM Agents over Live MCP Servers"
authors: Jerzy Kamiński, Ilya Galyukshev, Artem Kuznetsov, Sergey Chuprin, Kirill Redko, Aidar Shumbalov, Anna Kalyuzhnaya
year: 2026
venue: arXiv
url: https://arxiv.org/abs/2607.20531
code_url:
source: arxiv
collected_at: 2026-07-27
published_at: 2026-07-10
updated_at: 2026-07-10
status: queued
relevance: high
topics:
- agent-evaluation
- memory
- rag
- tool-use
methods:
-
benchmarks:
-
models:
-
datasets:
- cs.AI
related_concepts:
-
related_jobs:
-
related_experiments:
-
related_projects:
-
collection_score: 19
collection_queries: llm-agent, tool-use
---
## One-line Takeaway
Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
## Why Collected
- matched queries: llm-agent, tool-use
- inferred topics: agent-evaluation, memory, rag, tool-use
- arXiv categories: cs.AI
- collection score: 19
## Review Checklist
- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
- Does it include a benchmark, dataset, code, or reproducible experimental setup?
- Should it be promoted from `queued` to `skimmed` or `summarized`?
## Links
- arXiv: https://arxiv.org/abs/2607.20531