"Information on agent swarm architecture" matching MCP servers:

Enables GitHub-shaped tool calls to list issues, retrieve pull requests, and summarize them, while refusing merge-via-apply operations and remaining a local proof rather than making production changes.

An MCP server agent that enables analysis of YouTube videos by extracting transcripts, generating summaries, and creating chapter timestamps. It allows users to interact with video content through natural language to perform tasks such as writing social media posts.

An MCP server exposing document search, retrieval, and summarization tools, paired with a LangChain agent that performs multi-step tasks like finding and summarizing relevant docs.

Enables analysis of clinical trial protocols using MCP tools for document listing, entity extraction, adverse event clustering, and summarization.

A local-first MCP server that lets agents search and summarize a user's own WeChat history, with stable pagination, bulk chat workflows, unread/event queries, and gated enrichment tools.

A simple note storage system that lets users create and summarize notes with varying detail levels using Claude.

A hosted MCP server providing 15 media and data tools for AI agents, including web search, news, content extraction, summarization, translation, moderation, script writing, text-to-voiceover, transcription, subtitles, viral-clip discovery, and short-form video editing.

Enables automated video learning workflows by ingesting video URLs, managing remote GPU ASR transcription, pulling transcripts, generating digest summaries, and searching local notes via MCP tools.

Enables AI agents and developers to dynamically tokenize session context windows and compact dialogue history into structured outputs via MCP, CLI, or Python client. Runs on pure standard library Python with no external dependencies for deterministic, low-latency execution.

This MCP server enables users to analyze YouTube videos by extracting transcripts and generating specialized content like summaries, chapter timestamps, and social media posts.

Provides medical symptom extraction, differential diagnosis generation, PubMed literature search, and abstract summarization tools for LLM agents.

Enables natural language querying of Microsoft Fabric Data Warehouses with intelligent SQL generation, metadata exploration, and business-friendly result summarization. Features two-layer architecture with MCP-compliant server and agentic AI reasoning for production-ready enterprise data access.

Enables Claude to access fetched RSS news, event clusters, and archives to generate digests, watch for urgent alerts, and answer news-related queries via MCP tools.

Provides tools for fetching real-time news and performing AI-powered sentiment analysis and summarization using Mistral AI. It enables users to analyze news trends and extract structured insights through natural language queries.

Precise character-level string indexing for LLMs. Provides tools for finding, extracting, and manipulating text by exact character position to solve position-based operations.

A sophisticated research assistant that orchestrates a 5-step workflow of connected AI agents to provide deep research capabilities including question enhancement, web search, summarization, citation formatting, and result combination.

Enables MCP clients to search arXiv and OpenAlex literature and generate structured literature survey Markdown with normalized paper metadata.

Transcribe local audio/video to text + SRT/VTT with hosted Whisper large-v3, plus summaries, study notes, flashcards, document Q&A, and PDF compression. No API key required — runs via npx -y vocce-transcribe-mcp.

This MCP server performs multi-topic searches in business, news, finance, and politics using the Tavily API, providing high-quality sources and intelligent summaries.

An MCP-native document research agent that provides search, summarization, and citation tools for iterative multi-step research, ending in validated structured JSON reports.

Enables semantic search, retrieval, and summarization of Gmail emails with privacy-aware classification and PII sanitization.

A modular production-ready system that provides specialized agents for math, research, weather, and summarization tasks through a unified MCP toolbox with smart supervisor capabilities.

science agent for literature search and summary

Lets coding agents such as Claude Code and Codex hand summarising, field extraction, classification and OCR to the free, offline on-device model for Apple Foundation Models on macOS 27. One Rust binary, installed with Homebrew.

MCP server for koreafilings.com — AI-summarized Korean DART (전자공시) corporate disclosures, paid per call in USDC via the x402 protocol on Base. Tools: get_pricing (free), get_disclosure_summary (0.005 USDC).

Two self-hosted MCP servers: manage a local model machine (Ollama pull/switch, LoRA training) and bridge to local Ollama/vLLM for pure language processing tasks (writing, summarizing, classifying, extraction) without giving the calling agent tools or file access.

Lets any AI agent score and simplify its own text before it reaches a human, using Flesch readability metrics and plain-language rewrites entirely on the local machine.

A FastMCP server that enables AI assistants to extract structured information from unstructured text using Google's langextract library through a secure, optimized Model Context Protocol interface.

Model Context Protocol server exposing the bankstatementparser library as first-class agent tools for reading bank statements.

MCP Long Context Reader is a Python-based toolkit designed to overcome the context window limitations and high costs associated with Large Language Models (LLMs) processing extensive documents. It provides a FastMCP server with multiple, powerful strategies for an LLM agent to 'read' and query long documents without needing to load the entire text into its context window.