"Sort Content by Number of Downloads" matching MCP servers:

MCP server providing virtual memory for AI context with durable SQLite storage, retrieval, and bounded prompt assembly to manage context windows.

A meta-server that aggregates multiple MCP servers into a single interface, reducing token usage by 98%+ through progressive tool discovery and direct code execution that processes data between tools without consuming context window space.

A multi-agent orchestration system that enables multiple Claude instances to collaborate through a centralized hub with a shared workspace and real-time communication. It features integrated task management, role assignment, and persistent memory to facilitate complex, synchronized agent workflows.

This read-only MCP Server allows you to connect to Monday data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

This read-only MCP Server allows you to connect to SurveyMonkey data from Claude Desktop through CData JDBC Drivers. Free (beta) read/write servers available at https://www.cdata.com/solutions/mcp

This read-only MCP Server allows you to connect to Amazon Athena data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

This read-only MCP Server allows you to connect to MailChimp data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

An MCP Server that provides weather information by ZIP code using Interzoid's API, allowing agents to retrieve current weather conditions based on postal codes.

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Google Data Catalog (beta): https://www.cdata.com/download/download.aspx?sku=HGZK-V&type=beta

An MCP Server that provides access to League of Legends statistics via the SportData.io API, allowing agents to query and analyze LoL competitive gaming data.

Provides MCP tools to create and query SigNoz trace funnels, enabling agents to measure their own step conversion rates from within the agent loop.

Enables AI assistants to interact with the QuantConnect cloud platform for algorithmic trading. Supports creating and managing trading strategies, running backtests, deploying live algorithms, and performing comprehensive trading operations through the QuantConnect API.

Enables Claude Code instances to discover each other on a local machine and exchange messages instantly, with a broker that coordinates triage and delegation across a peer mesh.

Enables AI agents to respond to users with live, persistent, interactive web apps served at a single URL that evolve in place as the conversation continues. It exposes UI generation and evolution tools over MCP so agent responses can include clickable buttons and streaming interfaces alongside chat replies.

An MCP server that enables AI agents to execute real-world actions through 10 specialized engines covering authenticated API calls, browser automation, visual QA, shell commands, file operations, job scraping, and parallel task execution.

A discovery and routing layer for MCP servers that loads tool definitions on demand, reducing token usage by keeping servers out of the context window until needed.

Enables AI agents to search a curated directory of Claude Code agent skills, MCP servers, and plugin marketplaces ranked by community signal.

Enables MCP agents to submit content for human review via LoopQuest, returning verdicts asynchronously.

Enables thinking models to extend their reasoning by outsourcing parts of the chain of thought to a non-thinking model via the chat_agent tool, with configurable parameters.

Enables main agents to delegate memory retrieval, web research, and multi-step tasks to internal sub-agents, returning concise conclusions while keeping detailed tool calls and raw content out of the main context.