Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@AMiner MCP Server search for recent papers on quantum computing by John Preskill"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
语言 / Language: 🇨🇳 中文 | 🇺🇸 English
基于模型上下文协议（MCP）的服务器，通过 AMiner API 提供强大的学术论文搜索和分析功能。
关键词搜索 (search_papers_by_keyword) - 通过关键词搜索论文
期刊搜索 (search_papers_by_venue) - 搜索特定期刊/会议的论文
作者搜索 (search_papers_by_author) - 搜索特定作者的论文
高级搜索 (search_papers_advanced) - 多条件组合搜索
论文搜索助手 (paper_search_assistant) - 学术研究辅助的 AI 提示模板
分页支持（页码、每页数量）
排序选项（按年份或引用数）
详细论文信息展示
专业学术格式的英文界面
Related MCP server: AI Research Assistant - Semantic Scholar
添加到您的 MCP 客户端配置文件：
{
"mcpServers": {
"aminer": {
"command": "npx",
"args": ["-y", "@scipen/aminer-mcp-server"],
"env": {
"AMINER_API_KEY": "YOUR_AMINER_API_KEY"
}
}
}
}# 设置您的 AMiner API 密钥：
export AMINER_API_KEY="your_aminer_api_key_here"
# 使用 npx 启动
npx -y @scipen/aminer-mcp-server通过关键词搜索学术论文。
参数：
keyword (字符串，必需): 搜索关键词
page (数字，可选): 页码，默认 0
size (数字，可选): 每页论文数，默认 10，最大 10
order (字符串，可选): 排序方式：'year' 或 'n_citation'
示例：
{
"keyword": "深度学习",
"page": 0,
"size": 5,
"order": "n_citation"
}搜索特定期刊/会议发表的论文。
参数：
venue (字符串，必需): 期刊/会议名称
page (数字，可选): 页码，默认 0
size (数字，可选): 每页论文数，默认 10，最大 10
order (字符串，可选): 排序方式：'year' 或 'n_citation'
示例：
{
"venue": "Nature",
"page": 0,
"size": 10,
"order": "year"
}搜索特定作者发表的论文。
参数：
author (字符串，必需): 作者姓名
page (数字，可选): 页码，默认 0
size (数字，可选): 每页论文数，默认 10，最大 10
order (字符串，可选): 排序方式：'year' 或 'n_citation'
示例：
{
"author": "Geoffrey Hinton",
"page": 0,
"size": 10
}支持多条件的高级搜索。
参数：
keyword (字符串，可选): 搜索关键词
venue (字符串，可选): 期刊/会议名称
author (字符串，可选): 作者姓名
page (数字，可选): 页码，默认 0
size (数字，可选): 每页论文数，默认 10，最大 10
order (字符串，可选): 排序方式：'year' 或 'n_citation'
注意： 必须提供 keyword、venue 或 author 中的至少一个。
示例：
{
"keyword": "自然语言处理",
"author": "Yann LeCun",
"page": 0,
"size": 5,
"order": "n_citation"
}学术研究的 AI 助手提示模板。
参数：
research_topic (字符串，必需): 研究主题或领域
search_focus (字符串，可选): 搜索重点
recent: 关注最新论文
highly_cited: 关注高引用论文
comprehensive: 平衡搜索（默认）
示例：
{
"research_topic": "计算机视觉中的注意力机制",
"search_focus": "highly_cited"
}src/
├── index.ts # 主服务器文件
├── aminer-client.ts # AMiner API 客户端
└── types.ts # 类型定义pnpm run build - 构建项目
pnpm run start - 启动服务
pnpm run dev - 开发模式
pnpm run lint - 代码检查
pnpm test - 运行测试
运行时: Node.js 18+
语言: TypeScript
框架: Model Context Protocol SDK
包管理器: pnpm
API: AMiner 开放平台 API
协议: JSON-RPC 2.0 (MCP)
MIT 许可证
欢迎提交 Issues 和 Pull Requests！
如有问题和支持需求, 请添加小助手的企业微信：
Advanced paper search functionality supporting multiple search criteria
| Name | Required | Description | Default |
|---|---|---|---|
| keyword | No | Search keyword | |
| venue | No | Venue/journal name | |
| author | No | Author name | |
| page | No | Page number, starting from 0 | |
| size | No | Number of papers per page, maximum 10 | |
| order | No | Sort order: year (by publication year) or n_citation (by citation count) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the functionality without mentioning key traits like whether it's read-only, pagination behavior (implied by page/size parameters but not explained), rate limits, authentication needs, or error handling. This leaves significant gaps for an agent to understand how to use it effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Advanced paper search functionality') without unnecessary words. Every part earns its place by conveying the tool's scope and capability concisely.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (6 parameters, no output schema, no annotations), the description is incomplete. It lacks details on behavioral traits, usage context relative to siblings, and output format, making it inadequate for an agent to fully understand how to invoke and interpret results from this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal value beyond the input schema, which has 100% coverage with clear descriptions for all 6 parameters. It mentions 'multiple search criteria,' which aligns with parameters like keyword, venue, and author, but doesn't explain how they interact (e.g., AND/OR logic) or provide additional context not in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Advanced paper search functionality supporting multiple search criteria,' which specifies the verb (search), resource (papers), and scope (advanced with multiple criteria). However, it doesn't explicitly differentiate from sibling tools like search_papers_by_author, which focus on single criteria.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus the sibling tools (search_papers_by_author, search_papers_by_keyword, search_papers_by_venue). It mentions 'multiple search criteria' but doesn't clarify if this is for combined filters or as an alternative to the simpler single-criterion tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search papers published by a specific author
| Name | Required | Description | Default |
|---|---|---|---|
| author | Yes | Author name | |
| page | No | Page number, starting from 0 | |
| size | No | Number of papers per page, maximum 10 | |
| order | No | Sort order: year (by publication year) or n_citation (by citation count) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states the basic action without mentioning pagination behavior, rate limits, authentication needs, error handling, or what the search returns (e.g., paper details). For a search tool with no annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, clearly stating the tool's purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a search tool with 4 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits, usage context, and what to expect in results, making it inadequate for an agent to fully understand how to invoke and interpret this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description doesn't add any meaning beyond what the schema provides, such as explaining how author matching works or default behaviors. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Search papers published by a specific author,' which is a specific verb+resource combination. However, it doesn't explicitly distinguish this tool from its siblings (search_papers_advanced, search_papers_by_keyword, search_papers_by_venue), though the name implies differentiation by author versus keyword or venue.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools, prerequisites, or specific contexts where this search method is preferred over others like keyword or venue-based searches.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search academic papers by keyword
| Name | Required | Description | Default |
|---|---|---|---|
| keyword | Yes | Search keyword | |
| page | No | Page number, starting from 0 | |
| size | No | Number of papers per page, maximum 10 | |
| order | No | Sort order: year (by publication year) or n_citation (by citation count) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the basic action ('Search academic papers by keyword') without mentioning pagination behavior, rate limits, authentication requirements, error handling, or what the search results might look like. For a search tool with no annotation coverage, this leaves significant gaps in understanding its operational behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with just one sentence ('Search academic papers by keyword'), which is front-loaded and wastes no words. Every part of the sentence directly contributes to understanding the tool's purpose, making it efficiently structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a search function with 4 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't address key contextual aspects like result format, pagination details, search scope, or how it differs from sibling tools, leaving the agent with insufficient information to use it effectively beyond the basic schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with clear documentation for all parameters (keyword, page, size, order). The description doesn't add any meaningful parameter semantics beyond what's already in the schema, such as explaining search relevance, keyword matching logic, or default sorting. With high schema coverage, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Search academic papers by keyword', which includes a specific verb ('Search') and resource ('academic papers') with the method ('by keyword'). However, it doesn't differentiate from sibling tools like search_papers_by_author or search_papers_by_venue, which would require explicit comparison to achieve a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With sibling tools like search_papers_advanced, search_papers_by_author, and search_papers_by_venue available, there's no indication of when this keyword-based search is preferred or what its limitations are compared to more advanced or specific searches.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search papers published in a specific venue/journal
| Name | Required | Description | Default |
|---|---|---|---|
| venue | Yes | Venue/journal name | |
| page | No | Page number, starting from 0 | |
| size | No | Number of papers per page, maximum 10 | |
| order | No | Sort order: year (by publication year) or n_citation (by citation count) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the basic action ('Search papers') without detailing aspects like pagination behavior (implied by 'page' and 'size' parameters but not explained), rate limits, authentication needs, or what the search returns. For a tool with 4 parameters and no annotations, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Search papers published in a specific venue/journal'. It is front-loaded with the core purpose, has zero wasted words, and is appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, no annotations, no output schema), the description is incomplete. It lacks information on behavioral traits, usage guidelines, and output expectations. While the schema covers parameters well, the description fails to provide sufficient context for effective tool invocation and understanding of results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning all parameters are well-documented in the input schema. The description adds no additional meaning beyond what the schema provides (e.g., it doesn't explain parameter interactions or usage nuances). With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Search papers published in a specific venue/journal'. It specifies the verb ('Search') and resource ('papers'), and distinguishes the scope by venue/journal. However, it doesn't explicitly differentiate from sibling tools like search_papers_by_author or search_papers_by_keyword, which is why it doesn't reach a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like search_papers_advanced, search_papers_by_author, or search_papers_by_keyword, nor does it specify scenarios where this tool is preferred or excluded. This leaves the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0search_papers_advanced2 fields changedInput schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#"Input schema / additionalPropertiesAdded value: +falsesearch_papers_by_author2 fields changedInput schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#"Input schema / additionalPropertiesAdded value: +falsesearch_papers_by_keyword2 fields changedInput schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#"Input schema / additionalPropertiesAdded value: +falsesearch_papers_by_venue2 fields changedInput schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#"Input schema / additionalPropertiesAdded value: +falsesearch_papers_advancedsearch_papers_by_authorsearch_papers_by_keywordsearch_papers_by_venueScored across 4 tools
The tools are clearly distinguished by their search criteria (advanced, author, keyword, venue), making them easy to tell apart. However, 'search_papers_advanced' could potentially overlap with the others if it includes similar filters, but the descriptions specify distinct purposes.
All tool names follow a consistent 'search_papers_by_x' pattern, with 'search_papers_advanced' as a slight variation that still maintains readability. This uniformity helps agents predict and understand the tool set easily.
Four tools is reasonable for a paper search server, covering key search dimensions. It might be slightly thin if more operations like fetching paper details or citations are needed, but it's well-scoped for basic search functionality.
The server covers multiple search methods, which is good for its domain, but lacks CRUD operations like retrieving full paper details, downloading, or managing references. This could lead to dead ends for agents needing more than search results.
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