MCP Servers

Apollo's official MCP server that exposes GraphQL operations as MCP tools, letting AI agents interact with any GraphQL API through the Model Context Protocol. Turns curated GraphQL operations into callable tools, supports schema introspection, and can run locally alongside a graph via the Rover CLI or in production with the Apollo Runtime Container.

A collection of Apple-native tools exposed through the Model Context Protocol, letting AI assistants work with built-in macOS apps. Provides access to Messages, Notes, Contacts, Calendar, Reminders, Mail, and Maps so agents can send messages, create notes and events, and look up contacts directly on a Mac.

Arize AI's Phoenix, an open-source AI observability and evaluation platform, exposes a remote MCP endpoint that connects agents directly to a Phoenix instance. Lets assistants query OpenTelemetry traces and spans from LLM applications, inspect datasets and experiments, review evaluation results, and investigate latency or quality regressions.

DataStax's official MCP server for Astra DB, a serverless database built on Apache Cassandra with native vector search. Lets AI agents create and manage collections, insert and update records, and run similarity and metadata queries, making it a convenient backend for retrieval-augmented generation and agent memory workloads.

Auth0's official MCP server that connects AI agents to the Auth0 Management API. Lets developers create and configure applications, deploy Actions, manage APIs and connections, and query tenant logs using natural language. Runs locally with interactive tenant authentication and stores access tokens in the system keychain so the model never sees them directly, supporting secure Auth0 administration.

Microsoft's official MCP server for Azure DevOps. Brings Azure DevOps capabilities to AI agents, including managing work items and boards, browsing Git repositories and pull requests, querying builds and pipelines, and accessing wikis and test plans. Lets teams drive their Azure DevOps workflows through natural language from MCP-compatible tools.

The official Azure MCP Server brings Microsoft Azure to AI agents. It lets models query and manage Azure resources through natural language — Storage blobs and tables, Cosmos DB, Azure SQL, Key Vault, Monitor/Log Analytics (KQL), App Configuration, and more — and run Azure CLI commands, enabling cloud automation and infrastructure workflows directly from your tools.

BrowserStack's official MCP server for AI-assisted testing. Lets agents manage test cases, run manual and automated tests across real browsers and devices, access debugging artifacts such as logs and session details, and triage failures using plain English. Useful for cross-platform QA and browser-compatibility workflows from MCP-enabled clients.

Chrome's official MCP server for inspecting and controlling a live browser through Chrome DevTools. It helps agents diagnose UI, network, performance, and runtime issues.

Google Cloud's MCP server for deploying and managing applications on Cloud Run, giving coding agents a guided path from source code to a serverless production service.

A Model Context Protocol server that provides a natural-language interface for LLMs and agents to manage, monitor, and query data in CockroachDB. Supports schema exploration, query plan inspection, and running SQL, with a read-only-by-default posture so agents can investigate a distributed SQL cluster safely.

A lightweight MCP server for a local ComfyUI instance that lets AI agents generate and iteratively refine images, audio, and video. Agents can submit workflows, override prompts and sampler parameters, poll job status, and retrieve outputs, which makes conversational iteration on a local diffusion pipeline practical.

Confident AI's official MCP server, connecting AI tools to the platform behind DeepEval for evaluating, observing, and iterating on LLM quality. Agents can trigger and read evaluation runs, inspect metric scores and failing test cases, manage golden datasets, and review production traces to close the loop between eval results and code changes.

Contentful's official MCP server for the Content Management API. Gives AI agents tools to create, edit, organize, and publish content, manage content models and assets, and work across spaces and environments. Useful for automating editorial workflows and content operations in a Contentful-backed headless CMS.

Dagster's MCP integration enables agents to inspect and operate data assets, jobs, schedules, and runs in modern data platforms.

Directus' MCP integration connects agents to headless CMS data, schemas, and operations for governed content and application workflows.

A Model Context Protocol server that enables AI agents to interact with Discord through a bot. Agents can send and read messages in channels, list servers and channels, and manage basic server interactions while keeping the user in control. Useful for community automation, notifications, and conversational workflows on Discord.

Community MCP server that provides privacy-friendly web search through DuckDuckGo, plus fetching and parsing of web page content into clean text. Lets AI agents look up current information and retrieve source pages without an API key, making it a lightweight option for research and retrieval workflows. Not affiliated with DuckDuckGo.

MCP server for reading and writing Excel workbooks without needing Microsoft Excel installed. Lets AI agents create workbooks and worksheets, read and write cell ranges, apply formulas and formatting, and build charts and pivot tables programmatically. Useful for automating spreadsheet generation, reporting, and data entry from an assistant.

An MCP server for fal.ai's hosted generative model catalog, letting assistants create images, video, music, and audio from natural language. Agents can pick a model, submit a generation request with parameters, poll long-running jobs, and retrieve the resulting media URLs directly in the conversation.

Firebase's MCP integration exposes Firebase project context and development workflows to coding agents for building, testing, and operating Firebase applications.