OpenNeuro MCP Server

The OpenNeuro MCP server bridges the gap between AI assistants and one of the largest open repositories of neuroimaging data. By exposing a GraphQL interface to the OpenNeuro API, it lets developers query MRI, MEG, EEG, iEEG, and ECoG datasets directly from conversational agents. This eliminates the need for custom API wrappers or manual data extraction, enabling rapid prototyping of research tools and educational applications that rely on real‑world neuroimaging data.

Problem Solved

Researchers and developers often face a tedious workflow: download raw neuroimaging files, parse complex metadata, and then re‑upload curated data to a tool or model. OpenNeuro’s public datasets are vast and richly annotated, but accessing them programmatically requires handling authentication, pagination, and diverse file formats. The MCP server removes these friction points by providing a single, standardized query endpoint that returns structured JSON results. This streamlines data discovery and integration into AI pipelines without exposing sensitive credentials or requiring deep knowledge of the underlying REST API.

Core Value for AI Assistants

• Unified Query Language: GraphQL lets the assistant ask precise questions—“What is the description of dataset ds000224?” or “List all files in snapshot 1.0.0”—and receive only the requested fields, reducing payload size and processing time.
• Zero‑Auth Access: Public OpenNeuro data is available without API keys, so the assistant can retrieve information on demand in real time.
• Schema Introspection: Developers can programmatically discover available queries and fields, enabling dynamic tool creation and auto‑completion features within the assistant’s UI.
• Dataset & Snapshot Navigation: The server supports querying datasets, snapshots, and file listings, allowing assistants to guide users through the data hierarchy or fetch specific files for analysis.

Key Features Explained

• GraphQL Query Tool: Executes arbitrary GraphQL queries against OpenNeuro, returning structured JSON.
• Schema Introspection: Provides metadata about the GraphQL schema so developers can build tooling that adapts to changes automatically.
• Dataset Access: Fetches high‑level dataset information (id, name, description, creation date) and deeper details such as participant demographics or acquisition parameters.
• File Listing: Retrieves file names, sizes, and paths within a snapshot, enabling downstream processing or downloading.
• No Authentication Required: Simplifies integration for educational demos and rapid prototyping.

Real‑World Use Cases

1. Research Assistant – An AI assistant can help neuroscientists locate relevant datasets, summarize their contents, and suggest preprocessing pipelines.
2. Educational Tools – Students can query datasets directly from a chat interface to explore neuroimaging data without installing specialized software.
3. Data Integration – A pipeline that pulls OpenNeuro metadata into a larger database can use the MCP server to keep data up‑to‑date automatically.
4. Rapid Prototyping – Developers can prototype analysis scripts or visualizations that consume OpenNeuro data in real time, testing hypotheses quickly.

Integration with AI Workflows

The MCP server is designed to be added to an assistant’s configuration via a simple JSON snippet. Once connected, the assistant gains new tools—such as —that can be invoked by natural language prompts. The assistant’s prompt engine can generate GraphQL queries, send them to the server, and then format the returned JSON into user‑friendly responses. Because the server exposes a standard SSE endpoint, it fits seamlessly into existing MCP client implementations without additional infrastructure.

Standout Advantages

• Open Source & MIT Licensed: Developers can freely adapt the server for internal tools or commercial products.
• Academic Citation Friendly: The MIT license with an academic citation requirement ensures proper attribution while encouraging widespread use in research.
• Cloudflare Workers Deployment: The server can be deployed globally with minimal effort, providing low‑latency access for users worldwide.

In summary, the OpenNeuro MCP server empowers AI assistants to tap into a rich neuroimaging resource with minimal setup, enabling researchers, educators, and developers to build smarter, data‑driven applications that accelerate scientific discovery.