一个通过模型上下文协议(MCP)集成DBLP计算机科学文献数据库的服务器,供大型语言模型使用。
<a href="https://glama.ai/mcp/servers/cm42scf3iv"> <img width="380" height="200" src="https://gips3.baidu.com/it/u=672547897,2500334884&fm=3081&app=3081&f=PNG?w=760&h=400" alt="MCP-DBLP MCP 服务器" /> </a>MCP-DBLP 通过模型上下文协议将 DBLP(数字文献与图书馆项目)API 集成到 LLM 中,使 AI 模型能够:
| 工具名称 | 描述 |
|---|---|
get_instructions | 获取使用说明和工作流程指导 |
search | 使用布尔查询在 DBLP 中搜索出版物 |
fuzzy_title_search | 使用模糊标题匹配搜索出版物 |
get_author_publications | 检索特定作者的出版物 |
get_venue_info | 获取关于出版物会议地点的详细信息 |
calculate_statistics | 从出版物结果生成统计数据 |
add_bibtex_entry | 通过 DBLP 键添加 BibTeX 条目到集合中 |
export_bibtex | 将收集的所有 BibTeX 条目导出到 .bib 文件中 |
通过此 表单 向作者提供反馈。
只需运行:
claude mcp add mcp-dblp -- uvx mcp-dblp
添加到您的 Claude Desktop 配置文件中:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.json{
"mcpServers": {
"mcp-dblp": {
"command": "uvx",
"args": ["mcp-dblp"]
}
}
}
git clone https://github.com/szeider/mcp-dblp.git
cd mcp-dblp
uv venv && source .venv/bin/activate
uv pip install -e .
然后配置 Claude Desktop:
{
"mcpServers": {
"mcp-dblp": {
"command": "uv",
"args": ["--directory", "/path/to/mcp-dblp/", "run", "mcp-dblp"]
}
}
}
使用说明可通过 get_instructions 工具获取。关键的工作流程点在工具描述中显示;调用该工具以获取完整细节。另见 instructions_prompt.md。
使用布尔查询字符串在 DBLP 中搜索出版物。
参数:
query (字符串,必需):可能包括布尔运算符 'and' 和 'or'(不区分大小写)的查询字符串max_results (数字,可选):返回的最大出版物数量,默认为 10year_from (数字,可选):出版年份的下限year_to (数字,可选):出版年份的上限venue_filter (字符串,可选):用于出版物会议地点的不区分大小写的子串过滤器(例如,'iclr')include_bibtex (布尔值,可选):是否在结果中包含 BibTeX 条目,默认为 false使用模糊标题匹配在 DBLP 中搜索出版物。
参数:
title (字符串,必需):出版物的完整或部分标题(不区分大小写)similarity_threshold (数字,必需):介于 0 和 1 之间的浮点数,1.0 表示完全匹配max_results (数字,可选):返回的最大出版物数量,默认为 10year_from (数字,可选):出版年份的下限year_to (数字,可选):出版年份的上限venue_filter (字符串,可选):用于出版物会议地点的不区分大小写的子串过滤器include_bibtex (布尔值,可选):是否在结果中包含 BibTeX 条目,默认为 false检索特定作者的出版物详情,使用模糊匹配。
参数:
author_name (字符串,必需):作者的完整或部分姓名(不区分大小写)similarity_threshold (数字,必需):介于 0 和 1 之间的浮点数,1.0 表示完全匹配max_results (数字,可选):返回的最大出版物数量,默认为 20include_bibtex (布尔值,可选):是否在结果中包含 BibTeX 条目,默认为 false检索关于出版物会议地点的详细信息。
参数:
venue_name (字符串,必需):会议地点名称或缩写(例如,'ICLR' 或全名)从一系列出版物结果计算统计数据。
参数:
results (数组,必需):每个对象至少包含 'title'、'authors'、'venue' 和 'year' 的出版物对象数组将 BibTeX 条目添加到集合中以便后续导出。
参数:
dblp_key (字符串,必需):来自搜索结果的 DBLP 键(例如,"conf/nips/VaswaniSPUJGKP17")citation_key (字符串,必需):在 .bib 文件中使用的引文键(例如,"Vaswani2017")行为:
将所有收集的 BibTeX 条目导出到 .bib 文件中。
参数:
path (字符串,必需):.bib 文件的绝对路径(例如,"/path/to/refs.bib")行为:
add_bibtex_entry 添加的所有条目保存到指定路径重要提示: BibTeX 条目直接从 DBLP 获取,并带有 10 秒超时保护,未经 LLM 处理、修改或虚构。这确保了文献数据的最大准确性和可信度。仅按指定修改引文键。如果请求超时,则返回错误消息且条目不会被添加到集合中。
我们的探索集中在两种解释问题类型,归纳性和对比性,在局部和全局环境中(Marques-Silva 2023)。归纳性解释(Ignatiev, Narodytska, and Marques-Silva 2019),对应于主项解释(Shih, Choi, and Darwiche 2018)和充分理由解释(Darwiche and Ji 2022),阐明了具体的决策实例,而对比性解释(Miller 2019; Ignatiev et al. 2020),对应于必要理由解释(Darwiche and Ji 2022),明确指出了未选择替代方案的原因。相反,全局解释(Ribeiro, Singh, and Guestrin 2016; Ignatiev, Narodytska, and Marques-Silva 2019)旨在揭示模型在各种输入下的决策模式。
我们的探索集中在两种解释问题类型,归纳性和对比性,在局部和全局环境中 \cite{MarquesSilvaI23}。归纳性解释 \cite{IgnatievNM19},对应于主项解释 \cite{ShihCD18} 和充分理由解释 \cite{DarwicheJ22},阐明了具体的决策实例,而对比性解释 \cite{Miller19}; \cite{IgnatievNA020},对应于必要理由解释 \cite{DarwicheJ22},明确指出了未选择替代方案的原因。相反,全局解释 \cite{Ribeiro0G16}; \cite{IgnatievNM19}旨在揭示模型在各种输入下的决策模式。
所有引用已成功导出到 BibTeX 文件:/absolute/path/to/bibtex/20250305_231431.bib
@article{MarquesSilvaI23,
author = {Jo{\~{a}}o Marques{-}Silva and
Alexey Ignatiev},
title = {No silver bullet: interpretable {ML} models must be explained},
journal = {Frontiers Artif. Intell.},
volume = {6},
year = {2023},
url = {https://doi.org/10.3389/frai.2023.1128212},
doi = {10.3389/FRAI.2023.1128212},
timestamp = {Tue, 07 May 2024 20:23:47 +0200},
biburl = {https://dblp.org/rec/journals/frai/MarquesSilvaI23.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@inproceedings{IgnatievNM19,
author = {Alexey Ignatiev and
Nina Narodytska and
Jo{\~{a}}o Marques{-}Silva},
title = {Abduction-Based Explanations for Machine Learning Models},
booktitle = {The Thirty-Third {AAAI} Conference on Artificial Intelligence, {AAAI}
2019, The Thirty-First Innovative Applications of Artificial Intelligence
Conference, {IAAI} 2019, The Ninth {AAAI} Symposium on Educational
Advances in Artificial Intelligence, {EAAI} 2019, Honolulu, Hawaii,
USA, January 27 - February 1, 2019},
pages = {1511--1519},
publisher = {{AAAI} Press},
year = {2019},
url = {https://doi.org/10.1609/aaai.v33i01.33011511},
doi = {10.1609/AAAI.V33I01.33011511},
timestamp = {Mon, 04 Sep 2023 12:29:24 +0200},
biburl = {https://dblp.org/rec/conf/aaai/IgnatievNM19.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@inproceedings{ShihCD18,
author = {Andy Shih and
Arthur Choi and
Adnan Darwiche},
editor = {J{\'{e}}r{\^{o}}me Lang},
title = {A Symbolic Approach to Explaining Bayesian Network Classifiers},
booktitle = {Proceedings of the Twenty-Seventh International Joint Conference on
Artificial Intelligence, {IJCAI} 2018, July 13-19, 2018, Stockholm,
Sweden},
pages = {5103--5111},
publisher = {ijcai.org},
year = {2018},
url = {https://doi.org/10.24963/ijcai.2018/708},
doi = {10.24963/IJCAI.2018/708},
timestamp = {Tue, 20 Aug 2019 16:19:08 +0200},
biburl = {https://dblp.org/rec/conf/ijcai/ShihCD18.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@inproceedings{DarwicheJ22,
author = {Adnan Darwiche and
Chunxi Ji},
title = {On the Computation of Necessary and Sufficient Explanations},
booktitle = {Thirty-Sixth {AAAI} Conference on Artificial Intelligence, {AAAI}
2022, Thirty-Fourth Conference on Innovative Applications of Artificial
Intelligence, {IAAI} 2022, The Twelveth Symposium on Educational Advances
in Artificial Intelligence, {EAAI} 2022 Virtual Event, February 22
- March 1, 2022},
pages = {5582--5591},
publisher = {{AAAI} Press},
year = {2022},
url = {https://doi.org/10.1609/aaai.v36i5.20498},
doi = {10.1609/AAAI.V36I5.20498},
timestamp = {Mon, 04 Sep 2023 16:50:24 +0200},
biburl = {https://dblp.org/rec/conf/aaai/DarwicheJ22.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{Miller19,
author = {Tim Miller},
title = {Explanation in artificial intelligence: Insights from the social sciences},
journal = {Artif. Intell.},
volume = {267},
pages = {1--38},
year = {2019},
url = {https://doi.org/10.1016/j.artint.2018.07.007},
doi = {10.1016/J.ARTINT.2018.07.007},
timestamp = {Thu, 25 May 2023 12:52:41 +0200},
biburl = {https://dblp.org/rec/journals/ai/Miller19.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@inproceedings{IgnatievNA020,
author = {Alexey Ignatiev and
Nina Narodytska and
Nicholas Asher and
Jo{\~{a}}o Marques{-}Silva},
editor = {Matteo Baldoni and
Stefania Bandini},
title = {From Contrastive to Abductive Explanations and Back Again},
booktitle = {AIxIA 2020 - Advances in Artificial Intelligence - XIXth International
Conference of the Italian Association for Artificial Intelligence,
Virtual Event, November 25-27, 2020, Revised Selected Papers},
series = {Lecture Notes in Computer Science},
volume = {12414},
pages = {335--355},
publisher = {Springer},
year = {2020},
url = {https://doi.org/10.1007/978-3-030-77091-4\_21},
doi = {10.1007/978-3-030-77091-4\_21},
timestamp = {Tue, 15 Jun 2021 17:23:54 +0200},
biburl = {https://dblp.org/rec/conf/aiia/IgnatievNA020.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@inproceedings{Ribeiro0G16,
author