这是LSD更新后的 MCP 服务器。此次更新的目的是为了有效地利用通过我们的 SDK定义为行程的动态工具。
Related MCP server: superhighway-mcp
这是使用我们的 SDK将正在运行的 MCP 服务器与您的帐户连接起来。
使用user和password两个术语的原因是因为您要连接的是我们的postgres 兼容数据库。
在您的主目录中，将 JSON 写入名为.lsd的文件，其中包含属性user和password以及您的电子邮件和来自您的个人资料的API 密钥。
{
"user": "<you@email.domain>",
"password": "<api_key>"
}或者，您可以设置环境变量LSD_USER和LSD_PASSWORD 。
$ export LSD_USER='you@email.domain'
$ export LSD_PASSWORD='<api_key>'**重要提示：**如果您在采用此方法时遇到错误，请检查环境变量集是否可以从 PATH 或 MCP 客户端调用它的进程访问。
https://www.pulsemcp.com/servers/lsd-so-internetdata
更多内容即将推出。
克隆此存储库
$ git clone https://github.com/lsd-so/mcp.git{
"mcpServers": {
// other MCP servers configured here...
"lsd": {
"command": "node",
"args": [
"/<path>/<to>/mcp/build/index.js"
]
}
}
}
对于您想要教会 MCP 客户端一项“技能”的情况，您可以通过LSD 之旅（那是什么？ ）来实现。
“trip” 是一个由 LSD 程序组成的已发布模块，无论它是通过与我们的本地浏览器交互还是直接发布 trip 而得到的。
您可以从自行车浏览器中使用我们的“点击语言”获取 LSD，点击右上角的转录器图标即可激活该功能：
或者按下Command+k （Linux/Windows 系统为Ctrl+k ）。完成后，您可以交互式地“提取”重复容器以及您感兴趣的字段：
使用生成的 LSD，您可以像这样编辑别名：
之后您可以使用该语言进行发布。
在工作台上，只需编辑即可发布行程。
了解用于连接网络的InternetData SDK 。或者，您也可以使用“创建您的互联网”简写版本开始使用。
$ yarn create your-internet或者，如果你更喜欢 npm
$ npm create your-internetSearch Brave for possibly relevant links to a query
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
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 mentions the tool searches for 'possibly relevant links,' which implies it's a read-only operation that returns search results, but doesn't disclose critical behaviors like rate limits, authentication needs, result format, pagination, or error handling. For a search tool with zero annotation coverage, this is insufficient.
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 and front-loaded, consisting of a single sentence that directly states the tool's function. Every word earns its place with no wasted information, making it easy for an agent to parse quickly.
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 operation with no output schema and no annotations), the description is incomplete. It lacks details on result structure, error cases, performance characteristics, or any behavioral context needed for effective use. The description alone doesn't provide enough information for reliable tool invocation.
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 meaning beyond the input schema. It implies the 'query' parameter is used to search Brave, but with 0% schema description coverage and only one parameter, the baseline is 4 for zero parameters; however, since there is one parameter and the description doesn't elaborate on its format, constraints, or examples, it doesn't fully compensate, warranting a score of 3.
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 with a specific verb ('Search') and resource ('Brave'), and identifies the output ('links to a query'). It distinguishes the tool's function from its siblings (find_trips, run_lsd) by focusing on web search. However, it doesn't explicitly differentiate from potential alternative search tools, keeping it at a 4 rather than a 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. It mentions 'possibly relevant links' but gives no context about when this search method is preferred over others, what types of queries it handles best, or any prerequisites for use. This leaves the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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.
brave_searchfind_tripsrun_lsdScored across 3 tools
The tools have unclear boundaries and overlapping purposes. 'brave_search' and 'find_trips' could both be interpreted as search tools, with the latter's lack of description making it ambiguous whether it searches for trips or performs another function. 'run_lsd' is completely opaque without a description, potentially overlapping with execution or processing roles.
The naming is mixed but readable. 'brave_search' and 'find_trips' follow a verb_noun pattern, while 'run_lsd' uses a verb_prefix style. There is no chaotic mixing of cases, but the conventions are not fully consistent across all tools.
With only 3 tools, the server feels thin for a general-purpose 'LSD MCP Server', suggesting an incomplete surface. The lack of descriptions for two tools makes it hard to assess scope, but the count is borderline too few for meaningful coverage of any substantial domain.
The server is severely incomplete. Based on the tool names, it appears to cover search and execution, but with no descriptions for 'find_trips' and 'run_lsd', there are significant gaps. It lacks any CRUD operations, lifecycle management, or clear domain coverage, making it impossible for agents to perform coherent workflows.
Driflyte MCP server which lets AI assistants query topic-specific knowledge from web and GitHub.
The Remote MCP server acts as a standardized bridge between LLM applications (like Claude, ChatGPT, and Cursor) and external services, enabling AI agents to access external tools and resources. Its primary capability is providing a centralized search tool to discover other MCP servers and their respective tools. Unlike local implementations, it runs remotely with OAuth authentication and permission controls for security.
Hosted MCP server for live public-data APIs and Skills for AI agents.
