Apollo MCP Server
Enable graph-based API orchestration with AI
Apollo MCP Server provides a standard way for AI models to access and orchestrate your APIs running with Apollo. It allows AI tools to securely interact with GraphQL APIs using approved, context-aware operations.
What is MCP?
Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to AI models like Large Language Models (LLM). MCP enables LLMs and AI agents to indirectly fetch data from external sources.
MCP follows a client-server architecture. MCP servers expose functions, called tools, that MCP clients can invoke.
What is Apollo MCP Server?
Apollo MCP Server is an implementation of an MCP server. It makes GraphQL API operations available to AI clients as MCP tools. You can use Apollo MCP Server with any GraphQL API.
The GraphQL operations can be configured from persisted queries, which are predefined, approved lists of operations that are registered with and maintained by a graph. The operations can also be determined by AI introspecting your graph schema.
Apollo MCP Server is deployable in local environments via Apollo's Rover CLI or in containerized services in your cloud infrastructure. It can expose an MCP endpoint using Streamable HTTP for communication with AI clients.
Benefits of Apollo MCP Server
Facilitates AI-enabled API orchestration. With Apollo MCP Server, AI models can act as intelligent orchestrators of their GraphQL API operations. By exposing GraphQL operations as distinct MCP tools, AI clients can dynamically chain these operations together, in combination with other MCP servers and tools to execute complex workflows and automate multi-step processes.
Streamlines AI integration with GraphQL. Developers can expose existing or new GraphQL API operations to AI clients without building complex custom integrations. By translating GraphQL functionalities into standardized MCP tools, Apollo MCP Server can significantly reduce the effort needed to connect AI to diverse data sources.
Enhances control and security over data access. By using pre-defined, pre-approved persisted queries, developers can maintain precise governance over which data and operations AI clients can access. This ensures that AI uses existing security protocols and data access policies.
Getting started
Follow the quickstart to get started!