Streaming platforms integrate ChatGPT, enabling users to find content via natural language instead of keyword searches. AI offers personalized recommendations through dialogue, enhancing discovery efficiency.....
The 'AI Booking for Flights & Hotels' feature in Umetrip App upgrades smart assistants from conversational interaction to business execution, enabling users to input needs via natural language for automatic search, filtering, and recommendations of optimal travel plans.....
Google Maps introduces the AI feature 'Ask Maps,' allowing users to ask personalized travel questions through natural language conversation, without complex filtering. Gemini technology upgrades the map from simple location search to an intelligent assistant capable of understanding complex instructions and solving real-world problems.
Google Maps launched a major update this Thursday, integrating the Gemini AI model, adding the new conversational search feature "Ask Maps," and upgrading "immersive navigation." Users can now ask questions in natural language, such as "Which coffee shop has convenient charging and doesn't require long queues?", and the map will understand complex needs, changing the way people explore and travel.
GREB is an intelligent code search tool that allows you to search for code using natural language, quickly and accurately, and is compatible with multiple AIs.
An AI-driven image collection and management tool that boosts efficiency by 10 times.
Get quick and timely answers through natural language searches.
Enhances natural language technologies for information retrieval and intelligent search in the NASA Science Mission Directorate (SMD).
Google
$0.7
Input tokens/M
$2.8
Output tokens/M
1k
Context Length
Alibaba
-
Bytedance
32
Anthropic
$105
$525
200
$0.8
$8
256
Chatglm
$16
128
Xai
Deepseek
$2
Tencent
$0.5
224
Huawei
Openai
$17.5
$70
$2.4
$9.6
$1050
8
$3.5
$10.5
16
spartan8806
This is a sentence transformer model fine-tuned based on sentence-transformers/all-mpnet-base-v2, which can map text to a 768-dimensional dense vector space and support various natural language processing tasks such as semantic similarity calculation, semantic search, and text classification.
Shuu12121
A multilingual code search model optimized based on the ModernBERT architecture, supporting semantic matching between natural language and code
Zwounds
Converts natural language queries into standard Boolean search expressions suitable for academic databases, helping researchers and librarians create properly formatted Boolean search queries.
VPLabs
A conversational embedding model optimized for e-commerce search, fine-tuned based on Stella Embed 400M v5, excelling at understanding natural language queries and matching relevant products
avemio-digital
This is a text embedding model obtained by fine-tuning the ModernBERT-base model on a JSON dataset based on the sentence-transformers framework. It can map sentences and paragraphs to a 768-dimensional dense vector space and is suitable for various natural language processing tasks such as semantic text similarity calculation and semantic search.
joe32140
This is a sentence transformer model based on answerdotai/ModernBERT-large, fine-tuned on the msmarco-co-condenser-margin-mse-sym-mnrl-mean-v1 dataset. The model can map sentences and paragraphs to a 1024-dimensional dense vector space and is suitable for various natural language processing tasks such as semantic text similarity calculation and semantic search.
estrogen
This is a sentence transformer model based on estrogen/ModernBERT-base-sbert-initialized, fine-tuned on the all-nli dataset. This model can map sentences and paragraphs to a 768-dimensional dense vector space, suitable for various natural language processing tasks such as semantic text similarity calculation and semantic search.
Sinaof1381
This is a Persian sentence embedding model based on sentence transformers, which can map Persian sentences and paragraphs to a 1024-dimensional dense vector space and support natural language processing tasks such as semantic search and text clustering.
PORTULAN
The Serafim 900m Portuguese sentence encoder is a dedicated model based on sentence-transformers. It can map Portuguese sentences and paragraphs to a 1536-dimensional dense vector space and supports natural language processing tasks such as semantic search and text clustering.
nasa-impact
Indus-Retriever is a dual-encoder sentence transformation model fine-tuned from the nasa-smd-ibm-v0.1 encoder model, specifically designed for natural language processing tasks under NASA's Science Mission Directorate (SMD) to enhance information retrieval and intelligent search capabilities.
microsoft
CodeBERT is a pre-trained model for programming languages and natural languages, based on the RoBERTa architecture, supporting functions like code search and code-to-document generation.
Redis MCP Server is a natural language interface service designed for Redis, supporting AI agents to query and manage Redis data through natural language, integrating the MCP protocol, and providing multiple data structures and search functions.
A document semantic search service based on the Qdrant vector database, supporting URL and local file imports and providing natural language query functions.
ClaudePost is an email management service that enables natural - language interaction through Claude, supporting functions such as searching, reading, and sending emails.
The Kibana MCP Server project is a community-maintained tool that allows MCP-compatible clients (such as Claude Desktop) to access Kibana instances through natural language or programming. It is based on the official API documentation of Elastic Kibana, providing functions such as security authentication, API endpoint management, and search execution, and supporting two interaction modes: tools and resources.
The arXiv MCP Server is a service based on the Model Context Protocol (MCP) that allows users to interact with the arXiv API using natural language, enabling functions such as retrieving academic article metadata, downloading PDF files, searching the database, and loading articles into the context of a large - language model (LLM).
The MCP server is used to centrally manage media management suites such as Sonarr, Radarr, Lidarr, Readarr, and Prowlarr, supporting natural language queries, cross - service search, download monitoring, and configuration analysis.
The Readwise MCP Server is a model context protocol service for accessing and interacting with the Readwise library, providing functions such as accessing highlighted notes, natural language search, and retrieving books and documents.
Amadeus MCP Server is a community-developed service that integrates Amadeus' flight search API through the Model Context Protocol (MCP), allowing users to query flight information through a natural language interface.
An intent-based MCP server for automatically mapping natural language queries to the correct sources of project documents, supporting intelligent search, task management, and project document organization.
An intelligent stock data query and analysis service based on the MCP protocol, providing functions such as stock information query, financial analysis, and industry search, and supporting natural - language interaction.
The Searchcraft MCP Server is a toolset based on the Searchcraft vertical search engine, used to manage documents, indexes, federations, access keys, and analytical data, and supports performing management operations through natural language instructions.
A tool designed for FIRST Robotics Competition teams, which can search multiple official document libraries such as WPILib, REV, and CTRE simultaneously, quickly obtain answers to programming and hardware configuration through natural language questions, and support VS Code integration and AI assistant optimization.
The Rijksmuseum MCP Server provides access to museum art collections through natural language interaction, supporting search, analysis, and image viewing functions.
An IMAP/SMTP email server based on the model context protocol, supporting email search, reading, sending, and management operations by AI assistants (such as Claude and Cursor) through natural language instructions.
The MoviePilot MCP server is a protocol implementation that connects large language models with the MoviePilot media library management system, supporting media search, subscription management, download control and other functions through natural language interaction.
A system integrating the Qdrant vector database and MCP server for storing and retrieving code snippets, supporting natural language search and semantic retrieval.
MCP-Memos is a memo tool based on the MCP protocol, designed specifically for developers. It supports quick recording and retrieval of text information without switching applications. It uses large language models to provide powerful fuzzy search capabilities, including semantic understanding, context awareness, and natural language query functions.
This project demonstrates how to use Google's Gemini 2.5 Pro model to interact with the flight search tool under the MCP protocol through the function call feature, enabling natural language queries for flight information and returning formatted results.
The Florentine.ai MCP Server allows AI agents to query MongoDB and MySQL databases through natural language, supporting functions such as multi - tenant data isolation, automatic schema exploration, and semantic vector search.
Archive Agent is an intelligent file indexing tool that supports searching and querying file content through natural language. It combines AI search (RAG engine), automatic OCR, and the MCP interface, and can handle various file types, including text, documents, PDFs, and images.
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