ArangoDB MCP Server

The ArangoDB MCP server bridges the gap between conversational AI assistants and a powerful multi‑model database. By exposing ArangoDB’s AQL engine, document collections, and administrative operations as first‑class MCP tools, it lets developers query, mutate, and inspect data directly from Claude or VS Code agents without leaving the chat interface. This removes the need to write boilerplate code for database connectivity, allowing rapid prototyping and data‑driven decision making in a single workflow.

At its core the server implements a set of intuitive tools that mirror common database actions: runs arbitrary AQL statements and returns results as JSON; , , and perform CRUD operations on named collections; and give developers programmatic control over schema changes. The backup tool () turns the entire database into a portable JSON dump, simplifying migrations or archival tasks. Each tool accepts parameters in natural language‑friendly forms and returns structured metadata, making the assistant’s responses immediately actionable.

Real‑world scenarios that benefit from this server include data exploration for machine learning pipelines, rapid prototyping of data‑centric features in web applications, and automated reporting where an AI assistant can pull the latest metrics directly from the database. In a VS Code setting, the MCP server integrates seamlessly with the Copilot agent, allowing developers to invoke database operations from the chat pane or inline code comments. The server’s TypeScript implementation ensures type safety and fast compilation, while its stdio interface keeps deployment lightweight.

Unique advantages of the ArangoDB MCP server are its native support for both document and edge collections, enabling graph queries alongside traditional CRUD operations. The ability to pass bind variables into AQL queries gives developers secure, parameterized access without exposing raw query strings. Moreover, the server’s configuration is fully declarative via a JSON file or Smithery installation, making it easy to spin up in CI/CD pipelines or local development environments. By turning database interactions into conversational commands, the server empowers developers to focus on higher‑level logic while delegating persistence concerns to a reliable, AI‑ready interface.