PulseMCP Server
PulseMCP 服务器
模型上下文协议 (MCP) 服务器,通过 PulseMCP API 提供发现和探索 MCP 服务器和集成的工具。
特征
使用筛选和分页功能列出可用的 MCP 服务器
按名称或功能搜索特定的 MCP 服务器
按集成类型过滤服务器
列出所有可用的集成
全面支持 TypeScript
Related MCP server: Notes MCP Server
安装
在 MCP 客户端中安装
将其添加到您的 MCP 客户端配置中,并根据客户的偏好进行调整。例如:
{
"mcpServers": {
"pulsemcp": {
"command": "npx",
"args": ["-y", "pulsemcp-server"]
}
}
}克隆存储库:
git clone <repository-url>
cd pulsemcp-server安装依赖项:
npm install构建项目:
npm run build用法
运行服务器
构建后即可直接运行服务器:
./build/index.js或者通过 npm:
npm start发展
观察开发过程中的变化:
npm run watch要检查服务器的 MCP 实现:
npm run inspector可用工具
列表服务器
列出具有可选过滤和分页功能的 MCP 服务器。
参数:
query(可选):用于过滤服务器的搜索词integrations(可选):用于过滤的集成数组count_per_page(可选):每页结果数(最大值:5000)offset(可选):分页时要跳过的结果数
例子:
{
"query": "toolhouse",
"integrations": ["github"],
"count_per_page": 10,
"offset": 0
}列表集成
列出所有可用的集成。此工具不接受任何参数。
响应格式
两种工具都返回具有以下结构的 JSON 响应:
list_servers 响应
{
"servers": [
{
"name": "Server Name",
"url": "https://example.com",
"external_url": "https://external-link.com",
"short_description": "Server description",
"source_code_url": "https://github.com/example/repo",
"github_stars": 123,
"package_registry": "npm",
"package_name": "package-name",
"package_download_count": 1000,
"integrations": [
{
"name": "Integration Name",
"slug": "integration-slug",
"url": "https://integration-url.com"
}
]
}
],
"total_count": 1,
"next": null
}list_integrations 响应
{
"integrations": [
{
"name": "Integration Name",
"slug": "integration-slug",
"url": "https://integration-url.com"
}
]
}错误处理
该服务器包括强大的错误处理功能:
参数无效
API 连接问题
速率限制
身份验证错误
错误以标准格式返回,并带有适当的错误代码和消息。
发展
项目结构
pulsemcp-server/
├── src/
│ └── index.ts # Main server implementation
├── build/ # Compiled JavaScript
├── package.json # Project configuration
└── tsconfig.json # TypeScript configuration依赖项
@modelcontextprotocol/sdk: ^0.6.0
axios:^1.7.9
TypeScript:^5.3.3
执照
阅读LICENSE.MD
贡献
打开 PR - 表现友善,您将获得奖励!
Available Tools
2 toolslist_integrationsB
List all available integrations
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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. 'List all available integrations' implies a read operation but doesn't specify whether this requires authentication, has rate limits, returns paginated results, or what format the output takes. For a tool with zero annotation coverage, this is insufficient behavioral context.
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 states exactly what the tool does with zero wasted words. It's appropriately sized for a simple list operation and front-loads the essential information 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?
For a zero-parameter list tool with no output schema, the description provides the minimum viable information about what the tool does. However, it lacks important context about authentication requirements, rate limits, pagination behavior, and output format that would help an agent use it correctly. The absence of annotations increases the need for descriptive completeness.
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 tool has 0 parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description doesn't need to add parameter information, and the baseline for this scenario is 4. The description appropriately focuses on the tool's purpose rather than redundant parameter details.
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 verb ('List') and resource ('all available integrations'), making the purpose understandable. However, it doesn't differentiate from the sibling tool 'list_servers' - both are list operations but for different resources, so the distinction is implicit rather than explicit.
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. There's no mention of prerequisites, timing considerations, or comparison to the sibling 'list_servers' tool. The agent must infer usage context from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_serversC
List MCP servers with optional filtering
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Search term to filter servers | |
| integrations | No | Filter by integration slugs | |
| count_per_page | No | Number of results per page (maximum: 5000) | |
| offset | No | Number of results to skip for pagination |
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. While 'List' implies a read operation, it doesn't specify whether this requires authentication, what format the results come in, whether there are rate limits, or how pagination works beyond the offset parameter. The description adds minimal behavioral context beyond the basic action.
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 - a single sentence that communicates the core functionality without any wasted words. It's front-loaded with the main purpose and efficiently mentions the filtering capability.
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 list tool with 4 parameters and no output schema, the description is insufficient. It doesn't explain what information is returned about servers, how results are structured, or provide any context about what 'MCP servers' are in this system. With no annotations and no output schema, more descriptive context would be helpful.
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, so all parameters are documented in the schema itself. The description adds no specific parameter semantics beyond mentioning 'optional filtering' which is already implied by the schema. This meets the baseline for high schema coverage where the description doesn't need to compensate.
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 ('List') and resource ('MCP servers'), making the tool's purpose immediately understandable. However, it doesn't differentiate from the sibling 'list_integrations' tool, which would require mentioning what distinguishes listing servers from listing integrations.
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 mentions 'optional filtering' which implies some usage context, but provides no explicit guidance on when to use this tool versus alternatives like 'list_integrations' or how to decide between filtering methods. No when-not-to-use scenarios or prerequisites are mentioned.
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
list_integrations - First observed
list_servers
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: list_integrations targets integrations, while list_servers targets MCP servers. There is no overlap in functionality or ambiguity between them, making it easy for an agent to select the correct tool based on the desired resource.
Both tools follow a consistent verb_noun pattern with 'list_' as the prefix, using snake_case throughout. This predictability enhances readability and reduces cognitive load for agents when scanning the tool set.
With only 2 tools, the server feels under-scoped for a PulseMCP Server, which might imply broader functionality. While the tools are clear, the count is too low to cover a comprehensive domain, potentially limiting agent capabilities without additional context.
The tool set is severely incomplete for a server likely intended to manage integrations and servers. There are no CRUD operations (e.g., create, update, delete) or detailed actions (e.g., get specific integration/server), leaving significant gaps that could cause agent failures in handling lifecycle tasks.
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