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Ontario Data

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An MCP server for discovering, downloading, querying, and analyzing datasets from Ontario's open data portals, allowing natural language questions and high-perf

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Описание

An MCP server for discovering, downloading, querying, and analyzing datasets from Ontario's open data portals, allowing natural language questions and high-performance analytics via DuckDB.

README

ontario-data-mcp

[!IMPORTANT]
Beta: This project is under active development. The data structure and tool interfaces may change. LLM-generated analysis may contain errors. Always verify critical findings against the returned source data.

This is an MCP server for discovering, downloading, querying, and analyzing datasets from Ontario's Open Data portals. It allows asking questions of the data in English (or Spanish, Chinese, French, etc).

It currently supports the Ontario, Toronto, Ottawa, Waterloo, Kitchener, and Region of Waterloo portals, and utilizes a shared DuckDB cache for fast SQL queries, statistical analysis, and geospatial operations.

Contributing

Contributions welcome! To get started, see Installation below.

Found a bug? Have an idea? Discovered something interesting? Open an issue here: https://github.com/sprine/ontario-data-mcp/issues

Features

  • find - search across supported Ontario open data portals
  • download - retrieve and cache datasets
  • query - run SQL, statistical, and geospatial analysis via DuckDB
  • validate — verify that data claims are supported by query results
  • A shared DuckDB cache for high-performance analytics

Architecture

flowchart TD
    Client["AI Client<br/>(Claude Code · VS Code · etc.)"]

    subgraph Server["ontario-data-mcp (FastMCP)"]
        direction TB

        subgraph Tools["MCP Tools"]
            direction LR
            T1["Discovery"]
            T2["Metadata"]
            T3["Retrieval"]
            T4["Querying"]
            T5["Geospatial"]
            T6["Quality & Validation"]
        end

        PC["Portal Clients<br/>CKANClient · ArcGISHubClient"]
        Cache[("DuckDB Cache<br/>~/.cache/ontario-data/")]

        Tools -->|"fan out to all portals"| PC
        T3 & T5 -->|"download → store"| Cache
        T4 & T6 -->|"SQL queries"| Cache
    end

    subgraph Portals["Open Data Portals"]
        direction LR
        CKAN["Ontario · Toronto<br/>CKAN API"]
        ArcGIS["Ottawa · Waterloo · Kitchener<br/>Region of Waterloo<br/>ArcGIS Hub"]
    end

    Client <-->|"MCP Protocol"| Tools
    PC -->|"CKAN 2.8"| CKAN
    PC -->|"OGC Records / Hub v3"| ArcGIS

Data flow: Discovery and metadata tools fan out to all portals in parallel. Retrieval tools download data and store it in a local DuckDB cache. Querying and quality tools run fast SQL locally against the cache — no repeated API calls.

Installation

With Claude Code

claude mcp add ontario-data -- uvx ontario-data-mcp

To auto-approve all tool calls (no confirmation prompts), add to your Claude Code settings:

{
  "permissions": {
    "allow": ["mcp:ontario-data:*"]
  }
}

Tools are annotated as read-only or destructive per the MCP spec. Download tools populate the local cache but are read-only (no remote mutations). Destructive tools (cache_manage, refresh_cache) only modify local cached data.

With VS Code

Add to .vscode/mcp.json:

{
  "mcpServers": {
    "ontario-data": {
      "command": "uvx",
      "args": ["ontario-data-mcp"]
    }
  }
}
From Source
git clone https://github.com/sprine/ontario-data-mcp
cd ontario-data-mcp
uv sync
uv run ontario-data-mcp

To connect from source to Claude Code:

Note: MCP subprocesses don't inherit your shell's PATH, so you must use the absolute path to uv (find it with which uv).

claude mcp add ontario-data -- /absolute/path/to/uv run --directory /path/to/ontario-data-mcp ontario-data-mcp

Supported Portals

All searches fan out to every portal by default — no need to select a portal. Dataset and resource IDs are prefixed with their portal (e.g. toronto:abc123).

Portal Platform Datasets
ontario CKAN ~5,700
toronto CKAN ~533
ottawa ArcGIS Hub ~665
waterloo ArcGIS Hub ~129
kitchener ArcGIS Hub ~219
region-waterloo ArcGIS Hub ~125

List of tools available to the AI agent

Discovery (5 tools)
Tool Description
search_datasets Search for datasets across all portals (or narrow with portal=)
list_portals List all available portals with platform type
list_organizations List government ministries with dataset counts
list_topics List all tags/topics in the catalogue
find_related_datasets Find datasets related by tags and organization
Metadata (4 tools)
Tool Description
get_dataset_info Get full metadata for a dataset (use prefixed ID like toronto:abc123)
list_resources List all files in a dataset with formats and sizes
get_resource_schema Get column schema and sample values for a datastore resource
compare_datasets Compare metadata side-by-side for multiple datasets (cross-portal)
Retrieval & Caching (4 tools)
Tool Description
download_resource Download a resource and cache it in DuckDB (use prefixed ID like toronto:abc123)
cache_info Cache statistics + list all cached datasets with staleness
cache_manage Remove a single cached resource or clear the entire cache
refresh_cache Re-download cached resources with latest data
Querying (4 tools)
Tool Description
query_resource Query a resource via CKAN Datastore API (remote)
sql_query Run SQL against the CKAN Datastore (remote)
query_cached Run SQL against locally cached data in DuckDB
preview_data Quick preview of first N rows of a resource
Data Quality (3 tools)
Tool Description
check_freshness Check if a dataset is current vs. its update schedule
profile_data Statistical profile using DuckDB SUMMARIZE
validate_result Validate that a data claim is supported by query results
Geospatial (3 tools)
Tool Description
load_geodata Cache a geospatial resource (SHP, KML, GeoJSON) into DuckDB
spatial_query Run spatial queries against cached geospatial data
list_geo_datasets Find datasets containing geospatial resources

MCP Resources

Resources the agent can read for context without calling a tool:

URI Description
ontario://cache/index List of all locally cached datasets with freshness info
ontario://dataset/{dataset_id} Full metadata for a specific dataset (supports prefixed IDs)
ontario://portal/stats Overview statistics across all data portals
ontario://schema/{table_name} Column schema, types, sample values, and type warnings for a cached table
ontario://guides/duckdb-sql DuckDB SQL reference for Ontario open data analysis

Prompts

Context-aware guided workflow prompts:

  • explore_topic — Guided exploration of a topic (fetches live catalogue context)
  • data_investigation — Deep dive into a specific dataset: schema, quality, statistics
  • compare_data — Side-by-side analysis of multiple datasets

Environment Variables

Variable Default Purpose
ONTARIO_DATA_CACHE_DIR ~/.cache/ontario-data DuckDB storage + log file location
ONTARIO_DATA_TIMEOUT 30 HTTP timeout in seconds
ONTARIO_DATA_RATE_LIMIT 10 Max CKAN requests per second

Development

uv sync
uv run python -m pytest tests/ -v

License

MIT — see LICENSE for the software.

Data accessed through this tool is provided under the following open government licences:

from github.com/sprine/ontario-data-mcp

Установка Ontario Data

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/sprine/ontario-data-mcp

FAQ

Ontario Data MCP бесплатный?

Да, Ontario Data MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Ontario Data?

Нет, Ontario Data работает без API-ключей и переменных окружения.

Ontario Data — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Ontario Data в Claude Desktop, Claude Code или Cursor?

Открой Ontario Data на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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