"Top trending MCP servers currently popular" matching MCP servers:

An MCP server that tracks trending AI models, datasets, and spaces on Hugging Face.

An MCP proxy that embeds tool definitions and returns only the top-k semantically relevant tools per query, reducing context usage and routing calls to upstream MCP servers.

Enables AI clients to search live documentation for popular developer libraries and return clean, source-cited summaries via a RAG pipeline.

Bridges NotebookLM's research capabilities with Claude's content generation, enabling creation of notebooks, deep research queries, and structured content output from URLs, PDFs, or trending topics.

Enables retrieval and cleaning of official documentation content for popular AI/Python libraries (uv, langchain, openai, llama-index) through web scraping and LLM-powered content extraction. Uses Serper API for search and Groq API to clean HTML into readable text with source attribution.

An MCP server that provides semantic memory on top of Qdrant vector search, with tools to store and retrieve information using embeddings.

A Model Context Protocol server that provides real-time hot trending topics from major Chinese social platforms and news sites.

An MCP server that fetches real-time documentation for popular libraries like Langchain, Llama-Index, MCP, and OpenAI, allowing LLMs to access updated library information beyond their knowledge cut-off dates.

Aggregates multiple third-party APIs into unified MCP tools, providing out-of-the-box access to 10 popular services including OpenWeather, Google Maps, GitHub, Notion, Spotify, and more. Enables users to interact with weather data, search places, manage repositories, create content, and access various web services through a single MCP server.

A Model Context Protocol server that enables LLMs to interact with databases (currently MongoDB) through natural language, supporting operations like querying, inserting, deleting documents, and running aggregation pipelines.

Enables AI clients to access aggregated multi-platform trending topics and RSS feeds, filter news by keywords, and perform natural-language analysis, sentiment insights, and trend prediction.

Provides AI agents with persistent memory and knowledge management through a comprehensive knowledge graph platform. Enables storing, searching, and managing entities, relationships, and observations with advanced features like trending analysis and smart ranking.

A server that enables web searches using different providers (currently Bing) and converts URL content to Markdown, with support for retrieving WeChat official account articles.

Exposes Perplexity AI's search capabilities to Claude, enabling real-time web search and information retrieval within the assistant. The project is currently in active development with plans to support Perplexity Spaces and multi-source data synthesis.

Enables searching and retrieving top stories and individual items from Hacker News, with access to scores, comments, authors, and timestamps.

Provides pre-indexed knowledge packs for popular technologies (Stripe, React, etc.) that MCP-compatible agents can subscribe to and search, delivering citation-grounded answers with hourly fresh indexes.

A Model Context Protocol server that allows LLMs to interact with web content through standardized tools, currently supporting web scraping functionality.

Enables semantic search across thousands of indexed educational YouTube videos covering topics like engineering, marketing, and strategy. It allows users to query insights from top creators directly through Claude Code using the Model Context Protocol.

An MCP Server that provides Retrieval-Augmented Generation (RAG) capabilities to surface the latest Unity API documentation (currently v6.x).

Docdex is a lightweight, local documentation indexer/search daemon. It runs per-project, keeps an on-disk index of your markdown/text docs, and serves top-k snippets over HTTP or CLI for any coding assistant or tool—no external services or uploads required.

Enables fact-checking of news headlines using Google Gemini AI and web search verification, and retrieves trending news topics from RSS feeds with comprehensive multi-source analysis.

Enables agents to search university rules via hybrid retrieval and reranking, returning the top three relevant source clauses for downstream use.

MCP Tools Server that bridges the Agent Service with data services, currently enabling knowledge base search via the kb_search tool.

Provides a unified interface for storing and querying vector databases, currently supporting Qdrant with self-embedding and semantic search.

An MCP server that retrieves and cleans official documentation for popular AI/Python libraries via web search and LLM processing, exposing a get_docs tool.

Enables AI clients to query and retrieve current technical documentation for popular agent frameworks such as LangChain, LlamaIndex, AutoGen, Agno, OpenAI Agents SDK, MCP, Camel-AI, and CrewAI through stdio or SSE.

Enables AI coding agents to search a security corpus, scan Terraform plan JSON for cited findings, and list sources via MCP tools grounded in CIS AWS Foundations and OWASP Top 10 CI/CD risks.

Enables Claude to search a local knowledge base covering the Dutch collective labour agreement for temporary agency workers and its surrounding regulations, returning relevant passages labelled as currently valid, historical, or open questions. Every answer cites its source—the law, the cao text, or the body that sets the amount—so outdated rules are never presented as current.

Open registry of agent instruction files — system prompts, skills, workflows, and domain packs. Exposes the OpenClaw registry via 4 MCP tools: search by keyword/category, fetch full instruction files, list categories, and get top-rated files. CC0 licensed, free to use.

Provides AI agents with a persistent long-term memory over a single SQLite file, letting them write, screen, consolidate, and recall notes across sessions without any generative LLM in the loop. Recall judges relevance, follows links between notes, and signals when memory is insufficient, so agents get one to three useful facts per question instead of a generic top-k list.