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chore: 文档优化，增加 ai 分析所需的本地新闻测试数据
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sansan
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| [🎯 Core Features](#-core-features) | [🚀 Quick Start](#-quick-start) | [🐳 Docker Deployment](#-docker-deployment) | [🤖 AI Analysis](#-ai-analysis-deployment) |
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|:---:|:---:|:---:|:---:|
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| [📝 Changelog](#-changelog) | [🔌 MCP Clients](#-mcp-clients) | [❓ FAQ & Support](#-faq--support) | [⭐ Related Projects](#-related-projects) |
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| [🔧 Custom Platforms](#custom-monitoring-platforms) | [📝 Keywords Config](#frequencywordstxt-configuration) | | |
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| [🔧 Custom Platforms](#custom-monitoring-platforms) | [📝 Keywords Config](#frequencywordstxt-configuration) | [🪄 Sponsors](#-sponsors) | |
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</div>
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@@ -102,8 +102,6 @@ This project uses the API from [newsnow](https://github.com/ourongxing/newsnow)
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</details>
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> This project uses the API from [newsnow](https://github.com/ourongxing/newsnow) to fetch multi-platform data
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## ✨ Core Features
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### **Multi-Platform Trending News Aggregation**
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@@ -474,7 +472,11 @@ AI conversational analysis system based on MCP (Model Context Protocol), enablin
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- Cross-platform data comparison (activity stats, keyword co-occurrence)
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- Smart summary generation, similar news finding, historical correlation search
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> No more manual data file browsing—AI assistant helps you understand the stories behind the news in seconds
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> **💡 Usage Tip**: AI features require local news data support
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> - Project includes **November 1-15** test data for immediate experience
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> - Recommend deploying the project yourself to get more real-time data
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>
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> See [AI Analysis Deployment](#-ai-analysis-deployment) for details
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### **Zero Technical Barrier Deployment**
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@@ -904,7 +906,41 @@ frequency_words.txt file added **required word** feature, using + sign
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<br>
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**Method 2:** (See Chinese version for detailed steps)
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**Method 2:**
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1. Open in PC browser https://botbuilder.feishu.cn/home/my-app
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2. Click "New Bot Application"
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3. After entering the created application, click "Process Design" > "Create Process" > "Select Trigger"
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4. Scroll down, click "Webhook Trigger"
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5. Now you'll see "Webhook Address", copy this link to local notepad temporarily, continue with next steps
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6. In "Parameters" put the following content, then click "Done"
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```json
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{
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"message_type": "text",
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"content": {
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"total_titles": "{{Content}}",
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"timestamp": "{{Content}}",
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"report_type": "{{Content}}",
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"text": "{{Content}}"
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}
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}
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```
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7. Click "Select Action" > "Send Feishu Message", check "Group Message", then click the input box below, click "Groups I Manage" (if no group, you can create one in Feishu app)
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8. Message title fill "TrendRadar Trending Monitor"
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9. Most critical part, click + button, select "Webhook Trigger", then arrange as shown in image
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10. After configuration, put Webhook address from step 5 into GitHub Secrets `FEISHU_WEBHOOK_URL`
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</details>
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@@ -1399,7 +1435,31 @@ docker exec -it trend-radar ls -la /app/config/
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## 🤖 AI Analysis Deployment
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TrendRadar v3.0.0 added **MCP (Model Context Protocol)** based AI analysis feature, allowing natural language conversations with news data for deep analysis. Best prerequisite for using **AI features** is running this project for at least one day (accumulate news data).
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TrendRadar v3.0.0 added **MCP (Model Context Protocol)** based AI analysis feature, allowing natural language conversations with news data for deep analysis.
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### ⚠️ Important Notice Before Use
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**Critical: AI features require local news data support**
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AI analysis **does not** query real-time online data directly, but analyzes **locally accumulated news data** (stored in the `output` folder)
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#### Usage Instructions:
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1. **Built-in Test Data**: The `output` directory includes news data from **November 1-15, 2025** by default for quick feature testing
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2. **Query Limitations**:
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- ✅ Only query data within available date range (Nov 1-15)
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- ❌ Cannot query real-time news or future dates
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3. **Getting Latest Data**:
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- Test data is for quick experience only, **recommend deploying the project yourself** to get real-time data
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- Follow [Quick Start](#-quick-start) to deploy and run the project
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- After accumulating news data for at least 1 day, you can query the latest trending topics
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---
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### 1. Quick Deployment
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@@ -1528,7 +1588,189 @@ Create `.cursor/mcp.json`:
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</details>
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(Additional client configs including VSCode/Cline/Continue, Claude Code CLI, MCP Inspector, and others available in Chinese version)
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<details>
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<summary><b>👉 Click to expand: VSCode (Cline/Continue)</b></summary>
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#### Cline Configuration
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Add in Cline's MCP settings:
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**HTTP Mode**:
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```json
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{
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"trendradar": {
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"url": "http://localhost:3333/mcp",
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"type": "streamableHttp",
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"autoApprove": [],
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"disabled": false
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}
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}
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```
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**STDIO Mode** (Recommended):
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```json
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{
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"trendradar": {
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"command": "uv",
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"args": [
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"--directory",
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"/path/to/TrendRadar",
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"run",
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"python",
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"-m",
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"mcp_server.server"
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],
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"type": "stdio",
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"disabled": false
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}
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}
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```
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#### Continue Configuration
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Edit `~/.continue/config.json`:
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```json
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{
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"experimental": {
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"modelContextProtocolServers": [
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{
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"transport": {
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"type": "stdio",
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"command": "uv",
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"args": [
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"--directory",
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"/path/to/TrendRadar",
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"run",
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"python",
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"-m",
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"mcp_server.server"
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]
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}
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}
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]
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}
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}
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```
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**Usage Examples**:
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```
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Analyze recent 7 days "Tesla" popularity trend
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Generate today's trending summary report
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Search "Bitcoin" related news and analyze sentiment
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```
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</details>
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<details>
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<summary><b>👉 Click to expand: Claude Code CLI</b></summary>
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#### HTTP Mode Configuration
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```bash
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# 1. Start HTTP service
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# Windows: start-http.bat
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# Mac/Linux: ./start-http.sh
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# 2. Add MCP server
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claude mcp add --transport http trendradar http://localhost:3333/mcp
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# 3. Verify connection (ensure service started)
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claude mcp list
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```
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#### Usage Examples
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```bash
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# Query news
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claude "Search today's Zhihu trending news, top 10"
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# Trend analysis
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claude "Analyze 'artificial intelligence' topic popularity trend for the past week"
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# Data comparison
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claude "Compare Zhihu and Weibo platform attention on 'Bitcoin'"
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```
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</details>
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<details>
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<summary><b>👉 Click to expand: MCP Inspector</b> (Debug Tool)</summary>
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<br>
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MCP Inspector is the official debug tool for testing MCP connections:
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#### Usage Steps
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1. **Start TrendRadar HTTP Service**:
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```bash
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# Windows
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start-http.bat
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# Mac/Linux
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./start-http.sh
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```
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2. **Start MCP Inspector**:
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```bash
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npx @modelcontextprotocol/inspector
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```
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3. **Connect in Browser**:
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- Visit: `http://localhost:3333/mcp`
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- Test "Ping Server" function to verify connection
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- Check "List Tools" returns 13 tools:
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- Basic Query: get_latest_news, get_news_by_date, get_trending_topics
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- Smart Search: search_news, search_related_news_history
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- Advanced Analysis: analyze_topic_trend, analyze_data_insights, analyze_sentiment, find_similar_news, generate_summary_report
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- System Management: get_current_config, get_system_status, trigger_crawl
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</details>
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<details>
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<summary><b>👉 Click to expand: Other MCP-Compatible Clients</b></summary>
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<br>
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Any client supporting Model Context Protocol can connect to TrendRadar:
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#### HTTP Mode
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**Service Address**: `http://localhost:3333/mcp`
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**Basic Config Template**:
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```json
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{
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"name": "trendradar",
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"url": "http://localhost:3333/mcp",
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"type": "http",
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"description": "News Trending Aggregation Analysis"
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}
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```
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#### STDIO Mode (Recommended)
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**Basic Config Template**:
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```json
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{
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"name": "trendradar",
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"command": "uv",
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"args": [
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"--directory",
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"/path/to/TrendRadar",
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"run",
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"python",
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"-m",
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"mcp_server.server"
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],
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"type": "stdio"
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}
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```
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**Notes**:
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- Replace `/path/to/TrendRadar` with actual project path
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- Windows paths use backslash escape: `C:\\Users\\...`
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- Ensure project dependencies installed (ran setup script)
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</details>
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## ☕ FAQ & Support
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@@ -1541,28 +1783,13 @@ Create `.cursor/mcp.json`:
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<summary><b>👉 Click to expand: Author's Note</b></summary>
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<br>
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Thanks for all support! Due to sponsor support, the **one-yuan donation** QR code has been removed.
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Thanks for all support! Due to 302.AI sponsorship, my personal **one-yuan donation** QR code has been removed.
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Previous **one-yuan supporters** are listed in the **Acknowledgments** section at the top.
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This project's development and maintenance require significant time, effort, and costs (including AI model fees). With sponsorship support, I can maintain it more confidently.
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Currently, major AI model prices are relatively affordable. If you don't have a suitable model yet, clicking **302.AI** below also supports the developer:
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<div align="center">
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<span style="margin-left: 10px"><a href="https://share.302.ai/mEOUzG" target="_blank"><img src="_image/icon-302ai.png" alt="302ai logo" width="100"/></a></span>
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</div>
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**Usage Process:**
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1. After registration and top-up, enter [Management Dashboard](https://302.ai/dashboard/overview) at top right
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2. Click [API Keys](https://302.ai/apis/list) on the left
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3. Find default API KEY at page bottom, click eye icon to view, then copy (Note: don't click the copy button on the far right)
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4. Cherry Studio has integrated 302.AI, just fill in API key to use (currently must fill key first to see complete model list)
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If you already have a suitable model, welcome to **register and try**~
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Currently, major AI model prices are relatively affordable. Welcome to register and try, you can **[click here to claim $1 free credit](#-sponsors)**.
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</details>
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@@ -1580,16 +1807,58 @@ If you already have a suitable model, welcome to **register and try**~
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## 🪄 Sponsors
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> 302.AI is a pay-as-you-go enterprise-level AI resource platform
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> Providing the latest and most comprehensive **AI models** and **APIs** on the market, plus various ready-to-use online AI applications.
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> **302.AI** is a pay-as-you-go enterprise-level AI resource platform
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> Providing the latest and most comprehensive **AI models** and **APIs** on the market, plus various ready-to-use online AI applications
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<div align="center">
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<span style="margin-left: 10px"><a href="https://share.302.ai/mEOUzG" target="_blank"><img src="_image/banner-302ai-en.jpg" alt="302ai banner" width="800"/></a>
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<a href="https://share.302.ai/mEOUzG" target="_blank">
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<img src="_image/banner-302ai-en.jpg" alt="302.AI" width="800"/>
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</a>
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</div>
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### 💰 302.AI New User Benefits
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> The $1 credit can be used to call various AI models (such as Claude, GPT, etc.)
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> This project's AI analysis features require AI model integration. See [AI Analysis Deployment](#-ai-analysis-deployment) for configuration tutorial
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[](https://share.302.ai/mEOUzG)
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<details id="sponsor-tutorial">
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<summary><b>👉 Click to expand: 302.AI Usage Tutorial</b></summary>
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### Step 1: Get API Key
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1. After registration, go to [Management Dashboard](https://302.ai/dashboard/overview) at top right
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2. Click [API Keys](https://302.ai/apis/list) on the left
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3. Find default API KEY at page bottom, **click eye icon to view**, then copy
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(⚠️ Note: Don't click the copy button on the far right)
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### Step 2: Configure in Cherry Studio
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1. Open Cherry Studio, go to settings
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2. Select **"302.AI"** as model provider
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3. Paste the API Key you just copied
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4. Click **Manage**, now you can use all supported AI models
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**Tip:** Cherry Studio has natively integrated 302.AI, you can see the complete model list after configuration.
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**Q: How long does $1 free credit last?**
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A: Depends on usage frequency and model selection, can run multiple test sessions.
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**Q: What after free credit runs out?**
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A: You can top up as needed, pay-as-you-go. Major AI model prices are now relatively affordable.
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</details>
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<br>
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---
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### Common Questions
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Reference in New Issue
Block a user