MCP Servers

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.

Honeycomb's MCP server that lets AI assistants query and analyze observability data, including events, traces, alerts (triggers), and boards. Agents can run queries against datasets, inspect columns and schemas, and cross-reference production behavior with the codebase to investigate incidents. Connects to Honeycomb via API key or OAuth.

Metabase's built-in MCP server that lets AI clients connect directly to a Metabase instance, scoped to the connecting user's permissions. Enables agents to discover databases and models, run queries, and retrieve results and dashboards so teams can ask questions of their business intelligence data in natural language.

Official MCP server for DuckDB and MotherDuck. Lets AI assistants run SQL analytics directly against local DuckDB files, in-memory databases, S3-hosted data, and MotherDuck cloud warehouses. Supports read and write queries, browsing database catalogs, and switching between connections on the fly, making it well suited for conversational data exploration and lightweight analytics.

Intuit's official MCP server for QuickBooks Online, exposing QBO accounting features as callable tools. Lets AI assistants read and write customers, invoices, bills, payments, and other entities, and pull financial reports such as profit and loss or balance sheet, so agents can answer bookkeeping questions and automate accounting workflows against live QBO data.

Sanity's official MCP server that connects structured content to AI agents. Provides tools to run GROQ queries, read and write documents, explore and deploy schemas, manage content releases, and generate images, all with full schema context. Available as a hosted remote server at mcp.sanity.io and works with MCP-compatible clients like Cursor, Claude Code, and VS Code.

Official MCP server for Qdrant vector search engine. Acts as a semantic memory layer enabling AI agents to store and retrieve information using vector similarity search. Supports storing text with metadata, semantic querying, configurable embedding models via FastEmbed, and both cloud-hosted and local Qdrant instances. Useful for building RAG pipelines, code search, knowledge bases, and long-term agent memory.

Official MCP server for interacting with MongoDB databases and MongoDB Atlas. Enables AI agents to query collections, run aggregations, manage indexes, inspect schemas, and perform CRUD operations. Also supports Atlas cloud management including cluster provisioning, database user management, performance advisor, and stream processing. Supports read-only mode for safe exploration.

Official PayPal MCP server for commerce and payments. Lets AI agents create and capture orders, issue invoices, process refunds, manage subscriptions, and query transactions and disputes via the PayPal APIs. Useful for building checkout integrations, automating billing, and reconciling payments from an AI assistant.

Official Elastic MCP server that connects AI agents to Elasticsearch data using the Model Context Protocol. Enables natural language interactions with Elasticsearch indices — querying, analyzing, and retrieving data without custom APIs. Supports both stdio and streamable-HTTP transports, and works with Elasticsearch 8.x/9.x clusters including Elasticsearch Serverless. Distributed as a Docker container image from the Elastic registry.

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.

Render's official MCP server for interacting with your Render cloud resources via LLMs. Lets agents list and inspect services, create and manage deploys, read logs and metrics, and query managed Postgres and Key Value instances. Useful for deploying, debugging, and monitoring applications hosted on Render directly from an MCP-compatible assistant.