nuclei-server MCP Server
nuclei-server MCP 服务器
模型上下文协议服务器
这是一个基于 TypeScript 的 MCP 服务器,实现了一个简单的笔记系统。它通过提供以下内容来演示 MCP 的核心概念:
用 URI 和元数据表示文本注释的资源
创建新笔记的工具
生成笔记摘要的提示
特征
资源
通过
note://URI 列出并访问笔记每个笔记都有标题、内容和元数据
用于简单内容访问的纯文本 MIME 类型
工具
create_note创建新的文本注释将标题和内容作为必需参数
将注释存储在服务器状态中
提示
summarize_notes- 生成所有存储笔记的摘要包含所有笔记内容作为嵌入资源
返回 LLM 摘要的结构化提示
Related MCP server: azure-devops MCP Server
发展
安装依赖项:
npm install构建服务器:
npm run build对于使用自动重建的开发:
npm run watch安装
要与 Claude Desktop 一起使用,请添加服务器配置:
在 MacOS 上: ~/Library/Application Support/Claude/claude_desktop_config.json在 Windows 上: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"nuclei-server": {
"command": "/path/to/nuclei-server/build/index.js"
}
}
}调试
由于 MCP 服务器通过 stdio 进行通信,调试起来可能比较困难。我们推荐使用MCP Inspector ,它以包脚本的形式提供:
npm run inspector检查器将提供一个 URL 来访问浏览器中的调试工具。
Available Tools
2 toolscancel_scanC
Cancel a running scan
| Name | Required | Description | Default |
|---|---|---|---|
| scanId | Yes | Scan ID to cancel |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Cancel' implies a mutation operation that stops an ongoing process, but the description doesn't address important behavioral aspects: whether cancellation is reversible, what permissions are required, what happens to partial scan results, or how to verify the scan was running. For a mutation tool with zero annotation coverage, this is inadequate.
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 maximally concise - a single four-word sentence that directly states the tool's purpose with zero wasted words. It's appropriately sized for a simple tool with one parameter and clear basic functionality.
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?
For a mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't address the tool's behavioral implications, error conditions, or relationship to the sibling 'start_scan' tool. The agent would need to guess about important aspects like what constitutes a 'running' scan, cancellation effects, and verification of success.
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 has 100% description coverage, with the single parameter 'scanId' clearly documented in the schema. The description doesn't add any parameter semantics beyond what's already in the schema, but since the schema does the heavy lifting, 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 action ('cancel') and target ('a running scan'), providing specific verb+resource. However, it doesn't differentiate from the sibling tool 'start_scan' beyond the obvious verb difference, missing an opportunity to clarify the relationship between these complementary operations.
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, prerequisites, or constraints. While the presence of 'start_scan' as a sibling suggests a workflow relationship, the description doesn't explicitly state this or provide any usage context beyond the basic action.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
start_scanC
Start a new nuclei scan
| Name | Required | Description | Default |
|---|---|---|---|
| target | Yes | Target URL or IP address | |
| template | No | Template to use for scanning | |
| rateLimit | No | Rate limit per second | |
| templatesDir | No | Directory with templates | |
| severity | No | ||
| timeout | No | Timeout in seconds | |
| concurrency | No | Concurrent requests | |
| proxyUrl | No | Proxy URL (e.g., socks5://127.0.0.1:1080) | |
| proxyType | No |
TDQS
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 states the tool starts a scan but fails to describe what happens during execution (e.g., whether it runs asynchronously, potential impacts on targets, or expected outputs). This leaves critical behavioral traits undocumented for a tool with security implications.
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 a single, front-loaded sentence ('Start a new nuclei scan') that directly conveys the core purpose without any wasted words. This efficiency makes it easy to parse, though it may lack depth.
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 (9 parameters, no annotations, no output schema, and security-related functionality), the description is insufficient. It doesn't cover behavioral aspects, output expectations, or usage context, leaving significant gaps for an AI agent to understand how to invoke it correctly and interpret 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?
The schema description coverage is 78%, which is relatively high, setting a baseline of 3. The description adds no additional parameter information beyond what the schema provides, such as explaining the relationship between parameters or typical values. It doesn't compensate for the 22% gap in coverage, but the schema handles most documentation.
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 action ('Start a new nuclei scan') with a specific verb ('Start') and resource ('nuclei scan'), making the purpose immediately understandable. However, it doesn't distinguish this from its sibling tool 'cancel_scan' or explain what a 'nuclei scan' entails, which prevents 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, nor does it mention prerequisites or context for initiating a scan. While it implies usage for starting scans, there's no explicit advice on timing, constraints, or how it relates to 'cancel_scan'.
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.
2 tool updates
- First observed
cancel_scan - First observed
start_scan
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one starts a scan and the other cancels it. There is no overlap or ambiguity between these operations, making it easy for an agent to select the correct tool for the intended action.
Both tools follow a consistent verb_noun pattern (start_scan, cancel_scan), using snake_case throughout. This predictable naming scheme enhances readability and reduces confusion for agents.
With only 2 tools, the server feels too thin for a scanning domain, as it lacks essential operations like retrieving scan results, listing scans, or configuring scans. This minimal set may force agents into dead ends or require workarounds.
The tool surface is severely incomplete for a nuclei scanning server. While start and cancel are basic actions, there are significant gaps: no way to get scan status, view results, list scans, or manage templates. This will likely cause agent failures in typical scanning workflows.
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