Paper Citation Record · LEDGER

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers

As of 7 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2607.14158.

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

pith.paper-citation-record.v1
2607.14158 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T05:42:25.486846Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

17 of 17 outbound references displayed

verified exact1
verified fuzzy0
unresolved16
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 926025c3-1e64-42b9-9d2a-0e4159cd66fe · outbound

This paper cites anthropic.com/news/model-context-protocol.

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers anthropic.com/news/model-context-protocol

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T05:42:24.344616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8f97e6f-fe16-4cd8-92b1-48df03953dd7 · outbound

This paper cites PowerDAG: Supervisory Agentic AI System for Automating Distribution Grid Analysis.

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers PowerDAG: Supervisory Agentic AI System for Automating Distribution Grid Analysis

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T05:42:24.413075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66511f3f-c925-4980-8fef-366cbafe6a81 · outbound

This paper cites an unresolved cited work.

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers Unresolved cited work

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T05:42:24.487381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f685eab3-9c16-4ea6-800a-1746ec42c586 · outbound

This paper cites ArXivabs/2511.14478(2025),https: //api.semanticscholar.org/CorpusID:283080836.

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers ArXivabs/2511.14478(2025),https: //api.semanticscholar.org/CorpusID:283080836

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T05:42:24.558968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88cdd765-754d-41f0-a01a-ece3bbfeb302 · outbound

This paper cites McGraw-Hill, New York, NY (1994).

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers McGraw-Hill, New York, NY (1994)

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T05:42:24.620287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e521a8f6-011b-426b-879d-6e3d51f959bf · outbound

This paper cites Springer, London, UK (2010).

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers Springer, London, UK (2010)

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T05:42:24.675634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd43388e-6afc-4aa6-9314-3d3d3558da3f · outbound

This paper cites an unresolved cited work.

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T05:42:24.735473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4b5efa1-d750-4ddc-9134-1d7b901ed584 · outbound

This paper cites an unresolved cited work.

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T05:42:24.871744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a37749c-6982-4e68-9447-67b23562b897 · outbound

This paper cites In: Proceedings of the 37th International Conference on Neural Information Processing Systems (2023).

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers In: Proceedings of the 37th International Conference on Neural Information Processing Systems (2023)

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T05:42:24.940612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ed8a193-c78a-4e3d-be2e-638f82ec3ac3 · outbound

This paper cites https://doi.org/10.5547/01956574.43.1.bshi.

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers https://doi.org/10.5547/01956574.43.1.bshi

Reference 10

Resolution: verified exact; doi, observed 2026-08-02T05:43:26.628016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c94c3071-9238-4f63-946d-595237c6133e · outbound

This paper cites IEEE Transac- tions on Power Systems (2018).https://doi.org/10.1109/TPWRS.2018.2829021, https://arxiv.org/abs/1709.06743.

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers IEEE Transac- tions on Power Systems (2018).https://doi.org/10.1109/TPWRS.2018.2829021, https://arxiv.org/abs/1709.06743

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T05:42:25.021832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dcdc4444-cc68-481c-b4a2-62a4d8ededa6 · outbound

This paper cites Agentic Reasoning for Large Language Models.

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers Agentic Reasoning for Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T05:42:25.080053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e81c167-9977-4fba-9783-b9c8920cd216 · outbound

This paper cites arXiv preprint arXiv:2512.20789 (2025).

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers arXiv preprint arXiv:2512.20789 (2025)

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T05:42:25.133286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ce8eb94-2413-4e4b-8d52-ddfb0fae0b89 · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T05:42:25.278802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24e17a1d-fcbf-4bdb-8a94-86a811fd1403 · outbound

This paper cites Big Data and Cognitive Computing10(3), 68 (2026).

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers Big Data and Cognitive Computing10(3), 68 (2026)

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T05:42:25.352153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9193601-f385-47b5-9cf8-0997c623c71b · outbound

This paper cites In: ICLR (2023).

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers In: ICLR (2023)

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T05:42:25.410139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e3d6537-cefe-4037-82d5-9ebe8ebda2a9 · outbound

This paper cites EASYTOOL: Enhancing LLM-based Agents with Concise Tool Instruction.

Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers EASYTOOL: Enhancing LLM-based Agents with Concise Tool Instruction

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T05:42:25.486846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.