MCP-DBLP 一个通过Model Context Protocol (MCP) 提供对DBLP计算机科学文献数据库访问的服务器，适用于大型语言模型。 概述 MCP-DBLP通过Model Context Protocol将DBLP（数字文献库与图书馆项目）API与大型语言模型集成，使AI模型能够： 从DBLP数据库中搜索和检索学术出版物 处理引用并生成BibTeX条目 对出版物标题和作者姓名进行模糊匹配 提取和格式化书目信息 处理文档中的嵌入式引用 直接导出BibTeX以绕过LLM处理，从而实现最大准确性 特性 支持布尔查询的全面搜索功能 出版物标题和作者姓名的模糊匹配 直接从DBLP检索BibTeX条目 按年份和出版场所过滤出版物 出版数据的统计分析 直接导出BibTeX的能力，绕过LLM处理以实现最大准确性 可用工具 工具名称描述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获取关于出版场所的详细信息calculate_statistics从出版结果生成统计数据export_bibtex直接从DBLP导出BibTeX条目到文件 反馈 通过此表单向作者提供反馈。 系统要求 Python 3.11+ uv 安装 安装一个MCP兼容的客户端（例如，Claude Desktop应用） 安装MCP-DBLP： git clone https://github.com/username/mcp-dblp.git cd mcp-dblp uv venv source .venv/bin/activate uv pip install -e . 创建配置文件： 对于macOS/Linux： ~/Library/Application/Support/Claude/claude_desktop_config.json 对于Windows： %APPDATA%\Claude\claude_desktop_config.json 添加以下内容： \{ "mcpServers": \{ "mcp-dblp": \{ "command": "uv", "args": [ "--directory", "/absolute/path/to/mcp-dblp/", "run", "mcp-dblp", "--exportdir", "/absolute/path/to/bibtex/export/folder/" ] \} \} \} Windows: C:\\absolute\\path\\to\\mcp-dblp 提示 包含了一个instructions prompt，应与包含引用的文本一起使用。在Claude Desktop上，可以通过电气插头图标访问指令提示。 工具详情 search 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): 可能包含布尔运算符'and'和'or'的查询字符串（不区分大小写） max_results (数字, 可选): 要返回的最大出版物数量。默认为10 year_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): 出版场所的不区分大小写的子字符串过滤器（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 fuzzy_title_search 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，其中1.0表示完全匹配 max_results (数字, 可选): 要返回的最大出版物数量。默认为10 year_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)：对出版场所的不区分大小写的子字符串过滤器 include_bibtex (布尔值，可选)：是否在结果中包含BibTeX条目。默认为false get_author_publications 通过模糊匹配检索特定作者的出版物详情。 参数： author_name (字符串，必填)：作者的全名或部分名字（不区分大小写） similarity_threshold (数字，必填)：一个介于0和1之间的浮点数，其中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20 include_bibtex (布尔值，可选)：是否在结果中包含BibTeX条目。默认为false get_venue_info 检索关于某个出版场所的详细信息。 参数： venue_name (字符串，必填)：出版场所的名称或缩写（例如，“ICLR”或全称） calculate_statistics 从出版物结果列表中计算统计数据。 参数： results (数组，必填)：一个出版物对象数组，每个对象至少包含'title'、'authors'、'venue'和'year' export_bibtex 直接从DBLP导出BibTeX条目到本地文件。 参数： (string, required): HTML string containing one or more key links - Example: \`"Smith2023"\` Behavior: For each link, the BibTeX entry is fetched directly from DBLP Only the citation key is replaced with the key specified in the link text All entries are saved to a timestamped .bib file in the folder specified by --exportdir Returns the full path to the saved file Important Note: The BibTeX entries are fetched directly from DBLP with a 10-second timeout protection and are not processed, modified, or hallucinated by the LLM. This ensures maximum accuracy and trustworthiness of the bibliographic data. Only the citation keys are modified as specified. If a request times out, an error message is included in the output. Example Input text: Our exploration focuses on two types of explanation problems, abductive and contrastive, in local and global contexts (Marques-Silva 2023). Abductive explanations (Ignatiev, Narodytska, and Marques-Silva 2019), corresponding to prime-implicant explanations (Shih, Choi, and Darwiche 2018) and sufficient reason explanations (Darwiche and Ji 2022), clarify specific decision-making instances, while contrastive explanations (Miller 2019; Ignatiev et al. 2020), corresponding to necessary reason explanations (Darwiche and Ji 2022), make explicit the reasons behind the non-selection of alternatives. Conversely, global explanations (Ribeiro, Singh, and Guestrin 2016; Ignatiev, Narodytska, and Marques-Silva 2019) aim to unravel models' decision patterns across various inputs. Output text: Our exploration focuses on two types of explanation problems, abductive and contrastive, in local and global contexts \cite\{MarquesSilvaI23\}. Abductive explanations \cite\{IgnatievNM19\}, corresponding to prime-implicant explanations \cite\{ShihCD18\} and sufficient reason explanations \cite\{DarwicheJ22\}, clarify specific decision-making instances, while contrastive explanations \cite\{Miller19\}; \cite\{IgnatievNA020\}, corresponding to necessary reason explanations \cite\{DarwicheJ22\}, make explicit the reasons behind the non-selection of alternatives. Conversely, global explanations \cite\{Ribeiro0G16\}; \cite\{IgnatievNM19\} aim to unravel models' decision patterns across various inputs. Output Bibtex All references have been successfully exported to a BibTeX file at: /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@inproceedings\{DarwicheJ22, author = \{Adnan Darwiche and Arthur Choi\}, title = \{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科学书目数据库, https://dblp.org\} \} @article\{Miller19, author = \{Tim Miller\}, title = \{人工智能中的解释：来自社会科学的见解\}, 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计算机科学书目数据库, https://dblp.org\} \} @inproceedings\{IgnatievNA020, author = \{Alexey Ignatiev和 Nina Narodytska和 Nicholas Asher和 Jo\{\~\{a\}\}o Marques\{-\}Silva\}, editor = \{Matteo Baldoni和 Stefania Bandini\}, title = \{从对比解释到溯因解释再回到对比解释\}, booktitle = \{AIxIA 2020 - 人工智能进展 - 意大利人工智能协会第十九届国际会议, 虚拟活动, 2020年11月25-27日, 修订后的精选论文\}, 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计算机科学书目数据库, https://dblp.org\} \} @inproceedings\{Ribeiro0G16, author = \{Marco T\{\'\{u\}\}lio Ribeiro和 Sameer Singh和 Carlos Guestrin\}, editor = \{Balaji Krishnapuram和 Mohak Shah和 Alexander J. Smola和 Charu C. Aggarwal和 Dou Shen和 Rajeev Rastogi\}, title = \{"我为什么要信任你?": 解释任何分类器的预测\}, booktitle = \{第22届ACM SIGKDD知识发现与数据挖掘国际会议论文集, 美国加利福尼亚州旧金山, 2016年8月13-17日\}, pages = \{1135--1144\}, publisher = \{\{ACM\}\}, year = \{2016\}, url = \{https://doi.org/10.1145/2939672.2939778\}, doi = \{10.1145/2939672.2939778\}, timestamp = \{Fri, 25 Dec 2020 01:14:16 +0100\}, biburl = \{https://dblp.org/rec/conf/kdd/Ribeiro0G16.bib\}, bibsource = \{dblp计算机科学书目数据库, https://dblp.org\} \} ------ ## 免责声明 此MCP-DBLP处于原型阶段，使用时应谨慎。鼓励用户进行实验，但在关键环境中的任何使用风险自负。 ------ ## 许可证 此项目根据MIT许可证许可 - 详情请参阅[LICENSE](LICENSE)文件。