cnki-search
Click on "Install 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., "@cnki-searchSearch CNKI for 2023 PhD theses on 空间转录组"
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.
数据来自 search.cnki.com.cn 的公开检索接口,无需知网账号。检索范围是知网空间,不是 KNS 全部馆藏。
功能
工具 | 作用 |
| 按主题、篇名、关键词、全文或摘要检索;可限定作者、导师、年份、文献类型 |
| 根据检索得到的知网 / CDMD 链接读取摘要与学位信息 |
search 参数:
参数 | 取值 | 说明 |
| 字符串 | 检索词。仅查作者或导师时可为空 |
|
| 主题 / 篇名 / 关键词 / 全文 / 摘要 |
| 1–50 | 页码 |
| 字符串 | 作者 |
| 字符串 | 导师 |
| 如 | 年份 |
|
| 全部 / 期刊 / 博硕 / 博士 / 硕士 |
|
| 相关度 / 发表时间 / 下载 / 被引 |
已知题名时用 field=title。keyword 按词拆分,容易混入不相关结果。
返回 status:ok 为正常;blocked 为接口拒绝或校验页;error 为参数或网络错误。不要把 blocked 当成零结果。
Related MCP server: CNKI Search MCP Server
安装
请先让 Agent 阅读本仓库并按其中说明完成安装:
https://github.com/Biogod2020/cnki-search
需要本机已安装 uv(Python 3.12+)。Agent 读完后可用下面命令启动,无需事先 clone:
uvx --from git+https://github.com/Biogod2020/cnki-search.git cnki-search进程在 stdio 上等待 MCP 宿主,没有交互提示。
开发与测试:
git clone https://github.com/Biogod2020/cnki-search.git
cd cnki-search
uv sync --extra dev
uv run pytest -m "not live"联网回归:RUN_LIVE_CNKI=1 uv run pytest -m live -s
接入 MCP
把仓库链接交给 Agent,或把下面配置写入宿主。宿主会通过 uvx 拉取并运行。
{
"mcpServers": {
"cnki": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/Biogod2020/cnki-search.git",
"cnki-search"
]
}
}
}适用于 Claude、Cursor、Codex 及其他 MCP stdio 宿主。工具名:search、get_record。
接入 DeepSeek Harness
与 dsh-bing-search 相同:由 @deepseek-ai/dsh-mcp-client 拉起本仓库的 stdio 服务。发现后的工具名为:
mcp__cnki__search
mcp__cnki__get_record写入 cordis.yml 可用 examples/dsh.cordis.yml。写入 $DSH_HOME/profiles/<name>/cordis.patch.yml 时必须用 insert,否则 id 不存在会被静默跳过。见 examples/dsh.patch.yml:
- insert:
- id: mcp-cnki
name: '@deepseek-ai/dsh-mcp-client'
config:
serverName: cnki
transport: stdio
command: uvx
args:
- --from
- git+https://github.com/Biogod2020/cnki-search.git
- cnki-search
toolCallTimeoutMs: 30000
failOnStartupError: true
reconnect:
enabled: true
initialDelayMs: 500
maxDelayMs: 30000
maxAttempts: 10调用示例
{
"query": "SCA3发病年龄的临床预测模型构建与罕见变异关联研究",
"field": "title"
}{
"status": "ok",
"provider": "cnki",
"returned_count": 1,
"records": [
{
"title": "SCA3发病年龄的临床预测模型构建与罕见变异关联研究",
"url": "https://cdmd.cnki.com.cn/Article/CDMD-10533-1025564694.htm",
"authors": "彭林柳",
"year": "2023",
"kind": "博士论文"
}
]
}{
"query": "空间转录组",
"field": "title",
"kind": "thesis",
"sort": "date"
}Python:
from cnki_scholar import search_cnki, get_record
hits = search_cnki("影像组学 阿尔茨海默病", field="title", kind="thesis")
detail = get_record(hits.records[0].url)说明
覆盖范围为知网空间,新入库学位论文可能检索不到。
期刊可用接口的文献类型参数;博硕类型在解析后过滤。
列表页结构若变更,解析会失效。
文献版权归知网及原作者。请遵守知网使用条款与所在机构规定。
许可
MIT
Available Tools
2 toolsget_recordGet CNKI record metadataA
Fetch metadata from a 知网 / CDMD / cnki.com.cn record page. Not a PDF download.
Args: url: A CNKI Space or CDMD detail URL returned by search.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| url | Yes | |
| year | No | |
| error | No | |
| title | No | |
| degree | No | |
| status | Yes | |
| abstract | No | |
| provider | No | |
| institution | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the read-only nature ('Fetch metadata') and what it does not do ('Not a PDF download'), but lacks detail on return format, error behavior, or authentication. This is a moderate level of 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 brief: a one-line purpose, a negative clarification, and one-line parameter explanation. Every sentence adds value and it is front-loaded with the main purpose.
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?
This is a simple one-parameter get tool. An output schema exists (not shown), so return value explanation is not required. The description covers the parameter's format and source, and the 'Not a PDF' note prevents a common misuse. It is complete enough for a basic fetch operation.
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 only provides a 'url' string with no description. The description adds meaning by specifying 'A CNKI Space or CDMD detail URL returned by search', clarifying the required format and provenance. With 0% schema coverage, this compensation is valuable.
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 states 'Fetch metadata from a 知网 / CDMD / cnki.com.cn record page' with a specific verb and resource. It also distinguishes itself from PDF download and ties the input URL to a search result, clearly separating it from the sibling 'search' tool.
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?
It explicitly mentions the URL must be 'returned by search', implying a workflow where search is used first. It also warns 'Not a PDF download', which is an exclusion. However, it does not explicitly name the alternative or state when not to use, so slightly shy of full guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
searchSearch CNKI / 知网A
Search 知网空间 metadata. query may be empty if author or advisor is set.
Args: query: Search text. Exact title works best with field=title. field: theme (主题), title (篇名), keyword (关键词), content (全文), summary (摘要). page: Result page, starting at 1. author: Author name (作者). advisor: Thesis advisor (导师). year: Publication or degree year, e.g. 2023. kind: all, journal (期刊), thesis (博硕), phd (博士), master (硕士). sort: relevance, date, downloads, cites.
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No | all | |
| page | No | ||
| sort | No | relevance | |
| year | No | ||
| field | No | theme | |
| query | No | ||
| author | No | ||
| advisor | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| page | No | |
| error | No | |
| field | No | |
| query | Yes | |
| status | Yes | |
| records | No | |
| provider | No | |
| warnings | No | |
| elapsed_ms | No | |
| returned_count | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full burden of behavioral disclosure. It does explain parameter constraints (e.g., field enums, sort options) and a conditional rule about query emptiness, which is helpful. But it does not mention pagination size, error behavior for invalid combinations, or what happens when no filters are set. The output schema covers return values, but other behavioral traits remain undisclosed.
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 concise and well-structured: a one-line summary followed by an Args list with every line adding value. There is no redundant information, and the note about query emptiness is placed logically before the parameter list. It is appropriately sized for an 8-parameter tool.
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?
The description covers all parameters with semantics and provides a conditional note, which is solid for a search tool. An output schema exists, so return values are handled externally. However, it lacks explicit reference to sibling get_record for single-record lookups, and does not mention edge cases like page size limits or default field behavior beyond schema defaults. Minor gaps keep it from a perfect score.
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 provides meaningful explanations for all 8 parameters, going beyond the bare schema. It translates each enum value (theme, title, keyword, etc.), clarifies the meaning of 'page', and offers a practical tip ('Exact title works best with field=title'). This is exactly what parameter semantics should provide, and the schema alone offers no descriptions.
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 it searches 知网空间 metadata with a specific verb ('Search') and resource, and the parameter list distinguishes it from get_record by focusing on multi-field querying rather than single-record retrieval. The purpose is immediately understandable and not a tautology.
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?
There is a useful note about 'query may be empty if author or advisor is set', giving conditional usage guidance, and the parameter explanations imply how to use search. However, there is no explicit statement of when to use this tool versus get_record, nor any mention of alternatives or exclusions. This is a missed opportunity for clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
2 tool updates
v0.1.0- First observed
get_record - First observed
search
TDQS
The two tools are distinctly separated: 'search' performs queries across metadata fields, while 'get_record' fetches details from a specific URL returned by search. There is no functional overlap between them.
Both tool names follow a clear lowercase_with_underscores convention and use verb-first naming ('search', 'get_record'). The pattern is consistent and predictable.
With only two tools, the server is minimal. The scope (searching and retrieving CNKI records) is narrow enough to justify this count, but it borders on being too thin for a productive search API.
The server covers the essential metadata search and record retrieval workflows. It lacks features like citation export or full-text download, but for its stated purpose of metadata access, the coverage is adequate with only minor gaps.
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