Discover and integrate MCP servers tagged with reference-servers
13 reference-servers MCP Servers Available
An MCP server implementation for retrieving information from the AWS Knowledge Base using the Bedrock Agent Runtime.
An MCP server implementation that integrates the Brave Search API, providing both web and local search capabilities.
This MCP server attempts to exercise all the features of the MCP protocol. It is not intended to be a useful server, but rather a test server for builders of MCP clients. It implements prompts, tools, resources, sampling, and more to showcase MCP capabilities.
A Model Context Protocol server that provides web content fetching capabilities. This server enables LLMs to retrieve and process content from web pages, converting HTML to markdown for easier consumption.
Node.js server implementing Model Context Protocol (MCP) for filesystem operations.
A Model Context Protocol server for Git repository interaction and automation. This server provides tools to read, search, and manipulate Git repositories via Large Language Models.
MCP Server for the GitLab API, enabling project management, file operations, and more.
This MCP server integrates with Google Drive to allow listing, reading, and searching over files.
A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.
A Model Context Protocol server for retrieving and analyzing issues from Sentry.io. This server provides tools to inspect error reports, stacktraces, and other debugging information from your Sentry account.
An MCP server implementation that provides a tool for dynamic and reflective problem-solving through a structured thinking process.
A Model Context Protocol (MCP) server implementation that provides database interaction and business intelligence capabilities through SQLite. This server enables running SQL queries, analyzing business data, and automatically generating business insight memos.
MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.
MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.
MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.
Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.
