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., "@weibo-hot-search-mcp-server show today's hot search trends"
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.
This is a Weibo hot search data acquisition server based on the Model Context Protocol (MCP) framework, providing functions to fetch Weibo hot search list, hot search details, and comments.
Get Weibo Hot Search List
Display hot search rankings
Show hot search keywords
Show hot search index
Get Hot Search Details
Topic category
Topic description
Topic link
Topic claim information
Statistics (reads, discussions, interactions, original posts)
Get Hot Search Comments
Support getting comments from the first Weibo post or claim's post through hot search link
Configurable maximum comment fetch count
Display comment content and like count
Related MCP server: TrendRadar
Python >=3.10
Dependencies:
requests
lxml
mcp>=1.0.0
Clone the repository
git clone https://github.com/Yooki-K/weibo-mcp-server.gitInstall dependencies:
pip install -r requirements.txtNote: If using
uv run weibo_mcp_server, dependencies will be installed automatically, no need forpip install
pip install weibo-mcp-serverCreate a Weibo account, press F12 to open developer tools, and get the cookie as shown below:
Add this tool to the MCP server
On Windows: C:/Users/YOUR_USER/.cursor/mcp.json
{
"mcpServers": {
"weibo": {
"command": "uv",
"args": [
"--directory",
"path/to/weibo-mcp-server",
"run",
"weibo_mcp_server"
],
"env":{
"weibo_COOKIE": YOUR_WEIBO_COOKIE
}
}
}
}On Windows: %APPDATA%/Claude/claude_desktop_config.json
"weibo": {
"command": "uv",
"args": [
"--directory",
"/path/to/weibo-mcp-server",
"run",
"weibo_mcp_server"
],
"env": {
"weibo_COOKIE": YOUR_WEIBO_COOKIE
}
}MIT License - see LICENSE file for details.
Fork the repository
Create your feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add some amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request
Get hot search from weibo.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, and the description does not disclose any behavioral traits such as read-only nature, response format, or potential side effects. It is a bare statement that doesn't go beyond the tool's name.
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 concise sentence, front-loaded with the verb and resource, with no unnecessary words.
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 tool with no output schema and no annotations, the description is too minimal. It doesn't describe the return value, data structure, or any operational details, leaving the agent with only the name and one-liner. This is inadequate for even a simple 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 tool has zero parameters, so the schema description covers everything. The description adds no parameter explanations, but none are needed.
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 'Get hot search from weibo' which clearly identifies the action (get) and resource (hot search from weibo). It is distinct enough from siblings, though it does not explicitly clarify that this is the top-level list vs detail/comment.
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 information about when to use this tool instead of the sibling tools, nor any usage context such as prerequisites or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get hot search comment by url from weibo.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The url to search for. | |
| claim_id | No | The id of the claim. | |
| max_comments | No | The maximum number of comments to fetch, advised not too large. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosure. It only says 'Get', implying a read operation, but gives no information about safety, rate limits, authentication, pagination, or side effects. This is insufficient for a tool with no other metadata.
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 concise sentence, but it largely restates the tool name without adding meaningful differentiation or behavioral context. It is efficient but under-informative.
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?
With no annotations and no output schema, the description is too thin to provide complete context. It fails to explain return values, error conditions, or integration with sibling tools, which is needed for a tool with three parameters.
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 covers all three parameters with descriptions (100% coverage), so the baseline is 3. The description itself adds no additional parameter context beyond the schema, and the schema's descriptions are adequate.
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 a clear action ('Get') with a specific resource ('hot search comment') and identifies the input method ('by url'). It is distinguishable from sibling tools like WeiboGetHotSearchDetail by focusing on comments rather than general detail, though it does not explicitly contrast itself with them.
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 instead of the siblings. It merely states the function without any context or exclusions, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get hot search detail by word from weibo. Sometimes the word is not found, that's normal.
| Name | Required | Description | Default |
|---|---|---|---|
| word | Yes | The word to search for. |
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 transparently warns that the word may not be found, which is a useful behavioral trait. However, it does not disclose what 'detail' includes, whether it returns an error or empty result, or any other side effects. It adds some value but lacks comprehensive 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 two sentences, front-loaded with the primary purpose in the first sentence and a supplementary behavioral note in the second. Every word earns its place, with no fluff or redundancy. Excellent conciseness and structure.
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 simple 1-parameter get tool, the description is mostly complete: it states the action, resource, and scope, and even prepares the user for a common failure case. Since there is no output schema, it could benefit from clarifying what 'detail' contains, but for a low-complexity tool, this is a minor gap rather than a critical omission.
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 one parameter, 'word', with a description 'The word to search for.' The tool description also mentions 'by word,' but adds no additional meaning beyond the schema. Since schema description coverage is 100%, the baseline score of 3 applies; neither the schema nor the description provides extra semantic richness.
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 'Get hot search detail by word from weibo' clearly states the action (get), resource (hot search detail), and scope (by word). This distinguishes it from sibling tools like WeiboGetHotSearch (likely a list) and WeiboGetHotSearchCommentByUrl (comments), making the purpose unambiguous.
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 implies when to use this tool: when you have a specific word to look up in Weibo hot searches. It also provides an important usage note: 'Sometimes the word is not found, that's normal,' setting expectations for missing results. However, it does not explicitly mention alternatives or when not to use it, leaving room for clearer differentiation.
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.
v0.1.0WeiboGetHotSearchWeiboGetHotSearchCommentByUrlWeiboGetHotSearchDetailScored across 3 tools
Each tool clearly targets a distinct function: listing hot searches, retrieving details for a specific word, and fetching comments for a URL. There is no overlap in purpose, so an agent can easily choose the correct tool.
All tool names follow the same CamelCase pattern with the common prefix 'WeiboGetHotSearch' and a specific suffix indicating the operation (empty, Detail, CommentByUrl). This consistent naming convention makes the set predictable.
Three tools provide a concise, focused surface for the server's stated purpose of accessing Weibo hot searches. This is within the ideal range and each tool contributes a distinct capability without unnecessary bloat.
The tool set covers the core workflow of browsing hot searches: listing them, getting details for a word, and fetching comments via URL. No obvious gaps exist for the narrow domain of hot search consumption.
Weibo hot search, post search/details, comments/replies, users, posts, transcript.
搜索笔记、浏览首页推荐、查看笔记内容与评论，并发表你的评论。直接在工作流中与小红书内容互动，高效跟进话题。
Douyin hot search, work/user search, work details, comments/replies, profiles, series, transcript.
MCP server aggregating hot-search boards from 8 Chinese platforms (Weibo, Zhihu, Bilibili, Douyin).