dappier_real_time_searchLABSCO SUMMARY
The distinction here is licensing: the content behind the answers is rights-cleared and attributed to the publisher it came from.
Two tools cover both halves of the job — a live query answered from the web and market index, and a recommendation call that returns articles with source, date and relevance attached. Which body of content you get is decided by the model id you pass, so the same tool serves general web search, market data or one publisher's archive.
What it is
Dappier's own server over its rights-cleared data models: one tool answers a live query, the other returns recommended articles from a chosen content model.
What you get
- Direct answers to real-time questions — breaking news, weather, travel, deals, trending topics — from an AI-powered web index
- Stock market coverage in the same call shape: prices, financial headlines, trade signals and market summaries built on live Polygon.io data
- Content recommendations from domain-specific models, spanning sports, lifestyle and publisher-specific sources, selected by the model id you pass
- Structured results rather than prose: title, summary, publication date, source and domain, image preview where there is one, and a relevance score
- Control over how recommendations are picked — search algorithm choices of most_recent, semantic, most_recent_semantic or trending, a reference domain to favour, and how many results come back
- A marketplace of further data models, addressed by id through the same two tools
Requirements
A Dappier API key from platform.dappier.com, passed as DAPPIER_API_KEY. Published on PyPI as dappier-mcp and launched with uvx over stdio.
Setup effort
One command plus a key — pip install dappier-mcp, then supply credentials
USE CASES
01
Answering a question about right now
Ask directly — the weather in a city, the latest on a company — and get an answer from the live index.
02
Checking a stock before you comment on it
Query the market model for the price, the recent headlines and what moved.
03
Filling a feed with relevant articles
Ask the content model for recommendations and get titles, summaries, dates, sources and relevance scores back.
04
Keeping recommendations close to one site
Set the reference domain and how many of its articles must appear, and pick the search algorithm that fits — trending, semantic or most recent.
2 tools
Listed in project docs. Your client may show a different list.
dappier_ai_recommendationsBEFORE YOU INSTALL
What to know first
Tools you get
2 tools named in the project's documentation.
Requires
DAPPIER_API_KEY in your environment
INSTALLATION
Connect your client
Add the block to your client, or run the command directly.
Server setup
Configuration file
JSON
{
"mcpServers": {
"dappier": {
"command": "uvx",
"args": [
"dappier-mcp"
],
"env": {
"DAPPIER_API_KEY": "<YOUR_DAPPIER_API_KEY>"
}
}
}
}pip
TERMINAL
pip install dappier-mcp
