实现快速、免费的实时网页搜索，并访问来自值得信赖的媒体品牌的优质数据——新闻、金融市场、体育、娱乐、天气等等。使用 Dappier 构建强大的 AI 代理。
访问marketplace.dappier.com ，探索我们市场中的各种数据模型。
单击图像观看有关使用 Claude Desktop 设置 Dappier MCP 的完整视频指南。
Related MCP server: Deep Research MCP Server
获取 Dappier API 密钥。前往Dappier注册并生成 API 密钥。
要通过Smithery自动为 Claude Desktop 安装 dappier-mcp：
npx -y @smithery/cli install @DappierAI/dappier-mcp --client claude首先安装uv 。
MacOS/Linux ：
curl -LsSf https://astral.sh/uv/install.sh | sh窗户：
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"使用以下内容更新您的 Claude 配置文件（ claude_desktop_config.json ）：
{
"mcpServers": {
"dappier": {
"command": "uvx",
"args": ["dappier-mcp"],
"env": {
"DAPPIER_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}提示：您可能需要在
command字段中提供uvx可执行文件的完整路径。您可以在 macOS/Linux 上运行which uvx，或在 Windows 上where uvx来获取此路径。
配置文件位置：
macOS ： ~/Library/Application Support/Claude/claude_desktop_config.json
Windows ： %APPDATA%\Claude\claude_desktop_config.json
通过应用程序访问：
macOS 系统：
打开 Claude 桌面应用程序。
在菜单栏中，单击Claude > Settings 。
导航至Developer选项卡。
单击Edit Config以在默认文本编辑器中打开配置文件。
窗户：
打开 Claude 桌面应用程序。
单击齿轮图标访问Settings 。
导航至Developer选项卡。
单击Edit Config以在默认文本编辑器中打开配置文件。
注意：如果
Developer选项卡不可见，请确保您使用的是最新版本的 Claude Desktop。
使用以下内容更新 Cursor 配置文件（ mcp.json ）：
{
"mcpServers": {
"dappier": {
"command": "uvx",
"args": ["dappier-mcp"],
"env": {
"DAPPIER_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}提示：您可能需要在
command字段中提供uvx可执行文件的完整路径。您可以在 macOS/Linux 上运行which uvx，或在 Windows 上where uvx来获取此路径。
配置文件位置：
全局配置：
macOS ： ~/.cursor/mcp.json
Windows ： %USERPROFILE%\.cursor\mcp.json
项目特定配置：
将mcp.json文件放在项目文件夹内的.cursor目录中： <project-root>/.cursor/mcp.json
通过应用程序访问：
打开光标应用程序。
导航至Settings > MCP 。
单击Add New Global MCP Server 。
应用程序将在您的默认文本编辑器中打开mcp.json文件进行编辑。
注意：在 Windows 上，如果无法识别项目级配置，请考虑通过 Cursor 设置界面添加 MCP 服务器。
使用以下内容更新 Windsurf 配置文件（ mcp_config.json ）：
{
"mcpServers": {
"dappier": {
"command": "uvx",
"args": ["dappier-mcp"],
"env": {
"DAPPIER_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}提示：您可能需要在
command字段中提供uvx可执行文件的完整路径。您可以在 macOS/Linux 上运行which uvx，或在 Windows 上where uvx来获取此路径。
配置文件位置：
macOS ： ~/.codeium/windsurf/mcp_config.json
Windows ： %USERPROFILE%\.codeium\windsurf\mcp_config.json
通过应用程序访问：
打开 Windsurf 应用程序。
导航至Settings > Cascade 。
向下滚动到Model Context Protocol (MCP) Servers部分。
单击View raw config以在默认文本编辑器中打开mcp_config.json文件。
注意：编辑配置文件后，单击 MCP 服务器部分中的
Refresh按钮以应用更改。
Dappier MCP 远程服务器提供强大的实时功能，开箱即用，无需任何培训或微调。使用它来构建由最新网络数据、金融市场或 AI 精选内容驱动的实时交互式工具。
模特ID： am_01j06ytn18ejftedz6dyhz2b15
使用 Dappier 的 AI 索引实时搜索网络。实时访问：
来自全球各地的突发新闻
天气预报和当地更新
旅行警报和航班信息
热门话题和热门内容
网上优惠和购物亮点
非常适合新闻代理、旅行计划员、警报机器人等用例。
型号 ID： am_01j749h8pbf7ns8r1bq9s2evrh
此模型提供即时访问市场数据、财经新闻和交易洞察的功能。非常适合投资组合仪表盘、交易助手和投资工具。
它提供：
实时股票价格
财经新闻和公司动态
交易信号和趋势
市场动态摘要
使用 Polygon.io 的实时数据进行 AI 策划分析
从针对内容发现、摘要和提要生成而定制的几个特定领域的 AI 模型中进行选择。
型号： dm_01j0pb465keqmatq9k83dthx34
随时了解实时体育新闻、比赛回顾和专家分析。
模特ID： dm_01j0q82s4bfjmsqkhs3ywm3x6y
探索精选的生活方式内容——涵盖健康、娱乐和日常灵感。
型号： dm_01j1sz8t3qe6v9g8ad102kvmqn
您的智能狗护理助手——获取训练技巧、健康建议和行为见解。
模特ID： dm_01j1sza0h7ekhaecys2p3y0vmj
一个有关猫科动物一切事物的专家型人工智能——从营养到玩耍时间到日常梳理。
模特ID： dm_01j5xy9w5sf49bm6b1prm80m27
探索可持续的生活方式理念、道德选择和绿色创新。
模特ID： dm_01jagy9nqaeer9hxx8z1sk1jx6
了解超本地新闻、政治、文化、健康和多元文化更新。
每项建议包括：
清晰的标题和简洁的摘要
原始出版日期
受信任的来源和域
图像预览（如果有）
优先级的相关性分数
高级选项可让您：
调整搜索算法（ semantic 、 most_recent 、 trending等）
将结果集中在特定领域（ ref ）
调整您想要的结果数量（ similarity_top_k ， num_articles_ref ）
运行 MCP 检查器来调试服务器：
npx @modelcontextprotocol/inspector uvx dappier-mcp我们欢迎您为扩展和改进 Dappier MCP 服务器做出贡献。无论您是想添加新的搜索功能、增强现有功能还是改进文档，您的贡献都弥足珍贵。
有关其他 MCP 服务器和实现模式的示例，请参阅： https://github.com/modelcontextprotocol/servers
欢迎提交 Pull 请求！欢迎贡献新想法、错误修复或改进。
Fetch AI-powered recommendations from Dappier by processing the provided query with a selected data model that tailors results to specific interests.
- **Sports News (dm_01j0pb465keqmatq9k83dthx34):**
Get real-time news, updates, and personalized content from top sports sources.
- **Lifestyle News (dm_01j0q82s4bfjmsqkhs3ywm3x6y):**
Access current lifestyle updates, analysis, and insights from leading lifestyle publications.
- **iHeartDogs AI (dm_01j1sz8t3qe6v9g8ad102kvmqn):**
Tap into a dog care expert with access to thousands of articles covering pet health, behavior, grooming, and ownership.
- **iHeartCats AI (dm_01j1sza0h7ekhaecys2p3y0vmj):**
Utilize a cat care specialist that provides comprehensive content on cat health, behavior, and lifestyle.
- **GreenMonster (dm_01j5xy9w5sf49bm6b1prm80m27):**
Receive guidance for making conscious and compassionate choices benefiting people, animals, and the planet.
- **WISH-TV AI (dm_01jagy9nqaeer9hxx8z1sk1jx6):**
Get recommendations covering sports, breaking news, politics, multicultural updates, and more.
Based on the chosen `data_model_id`, the tool processes the input query and returns a formatted summary including article titles, summaries, images, source URLs, publication dates, and relevance scores.
| Name | Required | Description | Default |
|---|---|---|---|
| ref | No | The site domain where recommendations should be prioritized. | |
| query | Yes | The input string for AI-powered content recommendations. | |
| data_model_id | Yes | The data model ID to use for recommendations. Available Data Models: - dm_01j0pb465keqmatq9k83dthx34: (Sports News) Real-time news, updates, and personalized content from top sports sources like Sportsnaut, Forever Blueshirts, Minnesota Sports Fan, LAFB Network, Bounding Into Sports and Ringside Intel. - dm_01j0q82s4bfjmsqkhs3ywm3x6y: (Lifestyle News) Real-time updates, analysis, and personalized content from top sources like The Mix, Snipdaily, Nerdable and Familyproof. - dm_01j1sz8t3qe6v9g8ad102kvmqn: (iHeartDogs AI) A dog care expert with access to thousands of articles on health, behavior, lifestyle, grooming, ownership, and more from the industry-leading pet community iHeartDogs.com. - dm_01j1sza0h7ekhaecys2p3y0vmj: (iHeartCats AI) A cat care expert with access to thousands of articles on health, behavior, lifestyle, grooming, ownership, and more from the industry-leading pet community iHeartCats.com. - dm_01j5xy9w5sf49bm6b1prm80m27: (GreenMonster) A helpful guide to making conscious and compassionate choices that benefit people, animals, and the planet. - dm_01jagy9nqaeer9hxx8z1sk1jx6: (WISH-TV AI) Covers sports, politics, breaking news, multicultural news, Hispanic language content, entertainment, health, and education. | |
| num_articles_ref | No | Minimum number of articles to return from the reference domain. | |
| search_algorithm | No | The search algorithm to use for retrieving articles. | most_recent |
| similarity_top_k | No | Number of top similar articles to retrieve based on semantic similarity. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It describes the output as a 'formatted summary including article titles, summaries, images, source URLs, publication dates, and relevance scores,' which is helpful. However, it does not mention authorization requirements, rate limits, or side effects, which would be expected for a tool with no annotations.
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 starts with a clear purpose and organizes data models with bullet points, but it is somewhat verbose by repeating model information that is also in the schema. It is front-loaded but could be more concise, as every sentence earns its place but some repetition exists.
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 six parameters, no output schema, and 100% schema coverage, the description is nearly complete. It explains the output format and each data model's domain, covering the core functionality. It could be more complete by briefly explaining how ref, num_articles_ref, search_algorithm, and similarity_top_k affect results, but the schema handles those sufficiently.
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?
Schema description coverage is 100%, so the baseline is 3. The description adds value by naming and explaining data model IDs (e.g., 'Sports News: Real-time news...'), but these details are already present in the schema's description for data_model_id. Other parameters like ref, query, and search_algorithm are not elaborated beyond the schema, so the description provides minimal additional meaning.
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 'Fetch AI-powered recommendations from Dappier by processing the provided query with a selected data model,' which identifies the verb (fetch recommendations) and resource (Dappier data models). It distinguishes the tool from the sibling dappier_real_time_search by emphasizing recommendations with tailored content, though it doesn't explicitly contrast 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 implies usage by listing data models and their domains (e.g., Sports News, Lifestyle News), but it does not explicitly state when to use this tool over the sibling or provide conditions for use. It lacks exclusions or alternative suggestions, leaving the agent to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieve real-time search data from Dappier by processing an AI model that supports two key capabilities:
- Real-Time Web Search:
Access the latest news, weather, travel information, deals, and more using model `am_01j06ytn18ejftedz6dyhz2b15`.
- Stock Market Data:
Retrieve real-time financial news, stock prices, and trade updates using model `am_01j749h8pbf7ns8r1bq9s2evrh`.
Based on the provided `ai_model_id`, the tool selects the appropriate model and returns search results.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The search query to retrieve real-time information. | |
| ai_model_id | Yes | The AI model ID to use for the query. Available AI Models: - am_01j06ytn18ejftedz6dyhz2b15: (Real Time Data) Access real-time Google web search results, including the latest news, weather, travel, deals, and more. - am_01j749h8pbf7ns8r1bq9s2evrh: (Stock Market Data) Access real-time financial news, stock prices, and trades from Polygon.io, with AI-powered insights and up-to-the-minute updates. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behaviors. It mentions that an AI model is selected based on ai_model_id and returns results, but it does not address side effects, permissions, rate limits, error handling, or return structure. This is insufficient for full transparency.
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 concise, well-structured into two paragraphs, and front-loads the purpose. Every sentence adds value with no redundancy.
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 no output schema, no annotations, and two distinct models, the description lacks details on return format, error scenarios, and guidance on model selection. It is incomplete for effective agent use.
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?
Schema coverage is 100% with detailed descriptions for both parameters. The description adds no meaningful new information beyond what is already in the schema, so it meets the baseline without enhancement.
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 'Retrieve real-time search data from Dappier' and distinguishes between two specific capabilities (web search and stock market data) using model IDs. The tool name and description differentiate it from the sibling tool 'dappier_ai_recommendations' by focusing on real-time data retrieval.
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 lists two use cases but does not explicitly guide when to use this tool versus the sibling tool. It implies usage context through capabilities but lacks direct instructions or exclusions.
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.
v1.0.0dappier_ai_recommendationsdappier_real_time_searchScored across 2 tools
The two tools have clearly distinct purposes: one fetches AI recommendations with various data models, the other performs real-time search. No overlap in functionality.
Both tools share the 'dappier_' prefix and use descriptive noun phrases ('ai_recommendations', 'real_time_search'), though the first uses underscores between words and the second uses a more compound adjective form, leading to minor inconsistency.
With only 2 tools, the server is very focused. For a purpose-built API covering recommendations and search, this number is reasonable though minimal. Slightly under the typical 3-15 range but not drastically.
The server covers its stated domains (recommendations and real-time search) adequately, but lacks tools for managing data models or retrieving raw content. It's sufficient for basic use but leaves out potential CRUD operations.
Real-time data API for AI Agents: stocks, weather, forex, logistics, search, scrape, news, IP.
Free web search, 130M+ business records, local search, weather and travel data for AI agents.
Structured, cited, real-world data from 300+ sources and the open web for your AI agents.
Live web data for AI agents: structured JSON from 248 websites through one API key.
