data360-mcp by avsolatorio - MCP Server

Data360 MCP

A small Python package + FastMCP server that exposes World Bank Data360 search/metadata/data endpoints via the Model Context Protocol (MCP).

Overview

This repo provides:

A Python client module (data360.api) for calling Data360 endpoints.
An MCP server (data360.mcp_server) built on fastmcp that wraps those calls as MCP tools.

What is Data360?

The World Bank's Data360 Platform is a comprehensive data platform that provides access to thousands of development indicators from the World Bank. It is a platform for data discovery, exploration, and analysis.

Features

Search: POST to Data360 searchv2 and return typed results.
Metadata: Fetch metadata and available disaggregation options.
Data: Fetch indicator data (auto-paginates by skip).
MCP server: Exposes the functions above as MCP tools over streamable-http (default).

Project Structure

The package lives under src/data360:

src/data360/api.py: async Data360 API client functions
src/data360/config.py: pydantic-settings configuration (DATA360_* env vars)
src/data360/models.py: Pydantic request/response models
src/data360/mcp_server/*: FastMCP server definition + tool registration

Library API

The library entrypoint is data360.api.

Function	Description
`data360.api.search(...)`	Search for indicators/series via `searchv2`.
`data360.api.get_metadata(indicator_id, database_id, ...)`	Fetch series metadata and disaggregation options.
`data360.api.get_data(database_id, indicator_id, disaggregation_filters=None)`	Fetch indicator observations (auto-paginates).

Installation

Prerequisites

Python 3.10 or higher
uv (recommended) or pip

Using `uv` (recommended)

# Clone the repository
git clone <repository-url>
cd data360-mcp

# Install dependencies
uv sync

# Install editable
uv pip install -e .

Using pip

pip install -e .

Configuration

Configuration is read via pydantic-settings with the prefix DATA360_. Create a .env file (see .env.example) or export env vars.

# Required
DATA360_API_BASE_URL=https://data360api.worldbank.org

Environment Variables

Variable	Description	Required	Default
`DATA360_API_BASE_URL`	Base URL for the Data360 API	Yes	-
`DATA360_SEARCH_URL`	Override search endpoint URL	No	`${DATA360_API_BASE_URL}/data360/searchv2`
`DATA360_METADATA_URL`	Override metadata endpoint URL	No	`${DATA360_API_BASE_URL}/data360/metadata`
`DATA360_DISAGGREGATION_URL`	Override disaggregation endpoint URL	No	`${DATA360_API_BASE_URL}/data360/disaggregation`
`DATA360_DATA_URL`	Override data endpoint URL	No	`${DATA360_API_BASE_URL}/data360/data`
`DATA360_CODELIST_API_BASE_URL`	Override codelist base URL	No	`${DATA360_API_BASE_URL}/data360/metadata/codelist`

Usage

Running the MCP Server

Using the provided script

./run_server.sh

Using `poe` (task runner)

The repo defines a Poetry-like task via poethepoet:

uv run poe serve
uv run poe serve --transport streamable-http --port 8021

Using `uv` directly

uv run fastmcp run src/data360/server.py --transport streamable-http --port 8021

Using Python directly

uv run python -m data360.mcp_server --transport streamable-http --port 8021

The server binds on port 8021 by default. With streamable-http, clients typically connect at http://localhost:8021/mcp.

Using the Library Directly

import asyncio
import os

from data360 import api as data360_api

async def main():
  # Required configuration
  # os.environ["DATA360_API_BASE_URL"] = "https://data360api.worldbank.org"

    # Simple search
    result = await data360_api.search(
        query="food security",
        n_results=10
    )

    if result.error:
        print(f"Error: {result.error}")
    else:
        print(f"Found {result.count} results")
        for item in result.items or []:
            print(f"- {item.series_description.name} ({item.series_description.idno})")

asyncio.run(main())

Advanced Search with OData Filters

This will be abstracted away by the MCP tools and resources.

result = await data360_api.search(
    query="food security",
    n_results=20,
    filter="type eq 'indicator'",
    orderby="series_description/name",
    select="series_description/idno, series_description/name, series_description/database_id",
    skip=0,
    count=True
)

MCP Tools

The server exposes these tools (see src/data360/mcp_server/tools.py):

`data360_search_indicators`

Search for Data360 indicators using the World Bank Data360 API.

Parameters:

Parameter	Type	Required	Default	Description
`query`	string	Yes	-	Search query string to find relevant data series
`n_results`	integer	No	10	Number of top results to return (1-50)
`filter`	string	No	None	OData filter expression (e.g., `"type eq 'indicator'"`)
`orderby`	string	No	None	OData orderby expression (e.g., `"series_description/name"`)
`select`	string	No	None	OData select expression (e.g., `"series_description/idno, series_description/name"`)
`skip`	integer	No	0	Number of results to skip for pagination
`count`	boolean	No	False	Whether to include total count in response

Example Request:

{
  "query": "food security",
  "n_results": 20,
  "filter": "type eq 'indicator'",
  "orderby": "series_description/name",
  "select": "series_description/idno, series_description/name, series_description/database_id"
}

Example Response:

{
  "items": [
    {
      "@search.score": 14.934074,
      "series_description": {
        "idno": "UN_SDG_SN_ITK_DEFC",
        "name": "2.1.1 Prevalence of undernourishment",
        "database_id": "UN_SDG"
      }
    }
  ],
  "count": 1,
  "error": null
}

OData Query Syntax

The search endpoint supports OData query syntax for advanced filtering and selection:

Filter Examples

# Filter by type
filter="type eq 'indicator'"

# Filter by topic
filter="series_description/topics/any(t: t/name eq 'Health') and type eq 'indicator'"

# Multiple conditions
filter="type eq 'indicator' and series_description/database_id eq 'WB_WDI'"

Order By Examples

# Sort by name
orderby="series_description/name"

# Sort by name descending
orderby="series_description/name desc"

# Multiple sort fields
orderby="series_description/database_id, series_description/name"

Select Examples

# Select specific fields
select="series_description/idno, series_description/name, series_description/database_id"

# Select all fields from series_description
select="series_description/*"

Development

Setting Up Development Environment

# Clone the repository
git clone <repository-url>
cd data360-mcp

# Install development dependencies
uv sync --dev

# Install pre-commit hooks
pre-commit install

Running Tests

# There are currently no repo tests.
# If you add tests, run them like:
# uv run pytest

Code Quality

The project uses:

ruff: For linting and code formatting
pre-commit: For git hooks

# Format
uv run ruff format .

# Lint
uv run ruff check .

# Type check
uv run pyright

Repository Layout

.
├── src/
│   └── data360/
│       ├── api.py
│       ├── config.py
│       ├── models.py
│       ├── server.py
│       └── mcp_server/
│           ├── __main__.py
│           ├── _server_definition.py
│           ├── tools.py
│           ├── resources.py
│           └── prompts.py
├── run_server.sh
├── pyproject.toml
└── notebooks/example.ipynb

Integration Examples

With LangChain MCP Adapters

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient

client = MultiServerMCPClient({
    "data360": {
    "transport": "streamable_http",
        "url": "http://localhost:8021/mcp",
    }
})

async def search_indicators():
    async with client:
        tools = await client.get_tools()
        result = await client.call_tool(
          "data360_search_indicators",
            {
                "query": "poverty",
                "n_results": 10
            }
        )
        print(result)

asyncio.run(search_indicators())

License

See the file for details.

Support

For issues, questions, or contributions, please open an issue on the GitHub repository.

Acknowledgments

Built with FastMCP
Uses the Model Context Protocol specification
Integrates with the World Bank Data360 API