Paper Citation Record · LEDGER

MCPToolBench++: A Large Scale AI Agent Model Context Protocol MCP Tool Use Benchmark

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2508.07575.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2508.07575 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:16:35.372293Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 8e163f80-f762-439b-b2f0-97706eb0747a · inbound

Model Context Protocol (MCP) Tool Descriptions Are Smelly! Towards Improving AI Agent Efficiency with Augmented MCP Tool Descriptions cites this paper.

Model Context Protocol (MCP) Tool Descriptions Are Smelly! Towards Improving AI Agent Efficiency with Augmented MCP Tool Descriptions MCPToolBench++: A Large Scale AI Agent Model Context Protocol MCP Tool Use Benchmark

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T23:04:28.973528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1caa4c6-4ce2-41b5-94f6-60b5bf8456f0 · inbound

Bounded Autonomy for Enterprise AI: Typed Action Contracts and Consumer-Side Execution cites this paper.

Bounded Autonomy for Enterprise AI: Typed Action Contracts and Consumer-Side Execution MCPToolBench++: A Large Scale AI Agent Model Context Protocol MCP Tool Use Benchmark

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:20:11.016489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7573f259-6682-4913-8814-01e4ab279b3e · inbound

From Language to Action: Enhancing LLM Task Efficiency with Task-Aware MCP Server Recommendation cites this paper.

From Language to Action: Enhancing LLM Task Efficiency with Task-Aware MCP Server Recommendation MCPToolBench++: A Large Scale AI Agent Model Context Protocol MCP Tool Use Benchmark

Reference 70

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:21:26.753174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 43d881f9-c5d3-4b2a-b9f9-2c64fc00c615 · inbound

PAGER: Bridging the Semantic-Execution Gap in Point-Precise Geometric GUI Control cites this paper.

PAGER: Bridging the Semantic-Execution Gap in Point-Precise Geometric GUI Control MCPToolBench++: A Large Scale AI Agent Model Context Protocol MCP Tool Use Benchmark

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-20T18:48:53.344608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a3ab95a3-e293-465f-aa25-c26d30f8a905 · inbound

TOBench: A Task-Oriented Omni-Modal Benchmark for Real-World Tool-Using Agents cites this paper.

TOBench: A Task-Oriented Omni-Modal Benchmark for Real-World Tool-Using Agents MCPToolBench++: A Large Scale AI Agent Model Context Protocol MCP Tool Use Benchmark

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-19T20:47:45.960965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a14d0b4e-f880-4185-b1cf-f0495ab103b2 · inbound

Notation Matters: A Benchmark Study of Token-Optimized Formats in Agentic AI Systems cites this paper.

Notation Matters: A Benchmark Study of Token-Optimized Formats in Agentic AI Systems MCPToolBench++: A Large Scale AI Agent Model Context Protocol MCP Tool Use Benchmark

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T07:13:16.020360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 75f8d9f7-2a25-42d7-97b3-403b15312cce · inbound

Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Application cites this paper.

Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Application MCPToolBench++: A Large Scale AI Agent Model Context Protocol MCP Tool Use Benchmark

Reference 137

Resolution: verified exact; arxiv_id, observed 2026-06-27T09:50:48.434263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 89ee4932-e0ad-4eab-831e-e61d49505e89 · inbound

Mitigating Taint-Style Vulnerabilities in MCP Servers via Security-Aware Tool Descriptions cites this paper.

Mitigating Taint-Style Vulnerabilities in MCP Servers via Security-Aware Tool Descriptions MCPToolBench++: A Large Scale AI Agent Model Context Protocol MCP Tool Use Benchmark

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-07-09T10:26:11.138455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b13ba8a8-900e-4968-b83f-0f32fd7b55f7 · inbound

The Devil Is in the Interface: Evaluating How Tool Architecture Shapes Coding Agent Behavior cites this paper.

The Devil Is in the Interface: Evaluating How Tool Architecture Shapes Coding Agent Behavior MCPToolBench++: A Large Scale AI Agent Model Context Protocol MCP Tool Use Benchmark

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T14:16:35.372293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.