"A router for MCP (Model Context Protocol) tools" matching MCP servers:

Provides a bulk_read_files tool that reads specified files and forwards them to a remote backend for summarization, so agents receive concise summaries instead of raw file contents.

Summarizes Slack activity and GitLab merge requests with OpenAI to help generate daily standups, weekly reports, or quarterly check-ins.

A task-aware context compression layer for Agent workflows, RAG pipelines, and AI Coding assistants, reducing noisy logs, retrieval chunks, and code context into high-signal LLM inputs via CLI, Python SDK, and MCP.

Provides a suite of regex and text processing tools for AI agents, including pattern testing, extraction, and replacement with capture group support. It also enables various text transformations like case conversion, line sorting, and deduplication through the Model Context Protocol.

MCP stdio server that exposes 95 headless it-tools utilities (crypto, encoding, converters, generators, text, math, and more) through three routing tools (categories, list, execute), with flat JSON schemas, worked examples, and deterministic seeded execution designed for small router models.

A small MCP server that gives agents rich context about a YouTube video — its transcript, jump-to-the-moment deep links, metadata, and most-replayed moments — so they can answer questions, summarize, pull quotes, or surface highlights.

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.

Provides 14+ character-level text analysis tools that give LLMs the ability to accurately count letters, analyze individual characters, and work with text at the character level—overcoming tokenization limitations.

Enables AI assistants to search YouTube, fetch transcripts, and get AI summaries of videos without API keys.

An MCP server that enables users to read, search, and analyze PDF documents. It provides tools for extracting text, viewing metadata, searching content with context, and generating word statistics.

An AI-powered study assistant that generates quizzes, flashcards, summaries, and concept explanations from study materials using the Model Context Protocol.

The URL-Context-MCP MCP Server provides a tool to analyze and summarize the content of URLs using Google Gemini's URL Context capability via the Gemini API. Now also supports optional grounding with Google Search alongside URL Context. The server is designed to follow prompt-only orchestration: con

A simple notes MCP server that enables creating, listing, and summarizing text notes via resources, tools, and prompts.

Compresses, deduplicates, and filters tool outputs to optimize token usage and context window for AI agents.

The local PDF workflow for Claude Desktop and MCP hosts: fill, sign, merge, split, extract, and analyze PDFs without sending files to a web app.

An MCP server that provides developer knowledge and utility tools including local documentation search, text summarization, safe arithmetic calculation, unit conversion, and knowledge-base resources.

Enables AI agents to search, watch, summarize, clip, and extract transcripts from YouTube videos, all without needing an API key or leaving the chat.

Enables long-horizon autonomous agents to avoid context-window exhaustion by enforcing configurable token budgets and distilling older conversation turns into concise sliding summaries.

Enables autonomous agents to keep long-running conversations within configurable token budgets by compacting message arrays, preserving system instructions and recent turns while distilling older history into concise summaries. This prevents context window exhaustion without external LLM dependencies.

This TypeScript-based MCP server allows users to manage and interact with a note system through Model Context Protocol, enabling note creation and summarization with URIs and metadata.

Enables AI assistants to save, load, and search conversation context with AI-powered summarization and auto-tagging. Demonstrates semantic intent patterns and hexagonal architecture for maintainable AI-assisted development.

Enables LLM clients to search a firm's precedent vault and draft grounded contract clauses, legal memos, and document summaries.

An HTTP MCP server that indexes large documents into exact-line-numbered sections, enabling AI models to locate, read, summarize, and edit parts of a document without ingesting the whole file.

A read-only, local MCP server that enables Claude Desktop and Claude Code to brief users on selected WhatsApp chats, surfacing mentions, urgent items, follow-ups, bills, and payment screenshots through local OCR while keeping data encrypted on the user's PC.

A local-first Codex plugin that bundles an MCP server to safely interact with Mattermost, enabling channel/thread summarization, conversation search, and reviewed post publishing via the Mattermost REST API.

Enables Claude to read, rewrite, generate, and summarize LibreOffice Writer documents with preview-then-apply editing through MCP tools, authenticating via Claude Code login.

Fetches category data from a Q&A service API and returns a markdown summary grouped by category.

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.

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

Enables fetching, searching, and summarizing YouTube video transcripts with multi-language support.

Enables Chinese text segmentation using the jieba library with support for precise, full, and search engine modes. Provides natural language access to professional Chinese word segmentation capabilities through MCP protocol.

Enables sentiment analysis of text blocks using the Api Ninjas API, returning sentiment scores and overall sentiment classification for up to 2000 characters of text.

Provides various AI capabilities through DeepInfra's OpenAI-compatible API including image generation, text processing, embeddings, speech recognition, object detection, and classification tasks. Enables users to access multiple AI models for diverse tasks like generating images from prompts, transcribing audio, analyzing text sentiment, and performing computer vision operations.

Enables interactive AI chat through the Anthropic API, with document retrieval, slash commands, and extensible MCP tool integrations.

A Model Context Protocol server that provides tools for analyzing text documents, including counting words and characters. This server helps LLMs perform text analysis tasks by exposing simple document statistics functionality.

A Model Context Protocol server that enables retrieval of transcripts from YouTube videos with language-specific support.

A Model Context Protocol server that implements a simple notes system, allowing users to create, list, and summarize text notes.

Enables access to Humanizer APIs for text humanization with multiple models including basic, easy-use, and multi-language support. Requires API key authentication.

Provides access to Open Ai21 API services including chatbots (GPT-3.5, Claude 3, Llama 3), text-to-image generation, image background removal, text-to-speech, question answering, and text summarization capabilities.

Provides AI agents with comprehensive document parsing capabilities including PDF text extraction, OCR, HTML-to-markdown conversion, table extraction, and summarization, optimized for agent workflows.