OpenDataMCPConnect any Open Data to any LLM with Model Context Protocol.

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Reviewed by Daniel Nikulshyn·Updated July 2026

Overview

OpenDataMCP is a protocol that connects open data to large language models (LLMs) in minutes. It enables access to public datasets directly from LLM applications and facilitates publishing and distribution of open data. The protocol uses a Model Context Protocol (MCP) server that can be set up in an LLM application in a few clicks via a CLI tool. Users can access open data, publish their own datasets, and make them discoverable by the community. OpenDataMCP currently supports Claude and has plans to integrate with more LLMs.

Key features

Open Data Access
Publishing and distribution network
CLI tool for easy setup
Community-driven data contribution

Pricing

Model: Free
Category: MCP Servers
Rating: No reviews yet

Use cases

Accessing Public Datasets

Use OpenDataMCP to access public datasets directly from your LLM application, enabling querying and analysis of data from various sources.

Publishing Open Data

Publish your own datasets using OpenDataMCP's templates and guidelines, making them discoverable and accessible to the community.

Pros & Cons

Pros

Easy integration with LLMs
Access to multiple public datasets
Community-driven data publishing and distribution

Cons

Currently supports only Claude, with more LLM integrations planned
Requires technical setup for publishing datasets

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Q&A

What are the limitations?

Currently, OpenDataMCP only supports Claude, and publishing datasets requires technical setup.

Asked by Vikram Rao · Mar 25, 2026

Can I publish my own datasets?

Yes, users can publish their own datasets and make them discoverable by the community, using provided templates and guidelines.

Asked by Wei Chen · Mar 18, 2026

How is setup done?

Setup is done via a CLI tool in a few clicks, using commands like 'uvx odmcp setup PROVIDER_NAME'.

Asked by Robert Ainsworth · Feb 20, 2026

What LLMs are supported?

OpenDataMCP currently supports Claude and has plans to integrate with more LLMs.

Asked by Lucas Petit · Jan 14, 2026

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