Development Indicators MCP

Official10 tools

by lbruce-wq · Python

Open-source MCP for official development indicators with provenance and citations.

io.github.lbruce-wq/development-indicators — Model Context Protocol (MCP) Server

Open-source MCP server that provides official development indicators. The server is described as including provenance and citations, and is intended to surface indicator data with supporting source information for downstream use.

🛠️ Key Features

Open-source MCP
Official development indicators
Provenance and citations included

🚀 Use Cases

Fetch and consume official development indicators in MCP-enabled applications
Use cited/provenance-backed indicator values in research or reporting workflows

⚡ Developer Benefits

Indicator provenance and citations available alongside data
Clear alignment with “official development indicators” as the data scope

⚠️ Limitations

No additional tools, endpoints, indicator coverage, or implementation details were provided in the available server data.

Captured live from the server via tools/list.

list_sources

List supported and planned official data sources and their access characteristics.

Parameters1

topic

any

optional

Raw schema

{
  "type": "object",
  "properties": {
    "topic": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Topic"
    }
  },
  "title": "list_sourcesArguments"
}

get_source_setup

Explain source access requirements without exposing server secrets.

Parameters1

source_id

string

required

Raw schema

{
  "type": "object",
  "properties": {
    "source_id": {
      "title": "Source Id",
      "type": "string"
    }
  },
  "required": [
    "source_id"
  ],
  "title": "get_source_setupArguments"
}

find_microdata

Find relevant public microdata catalogues and state their access conditions.

Parameters2

query	string	required
country	any	optional

Raw schema

{
  "type": "object",
  "properties": {
    "query": {
      "title": "Query",
      "type": "string"
    },
    "country": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Country"
    }
  },
  "required": [
    "query"
  ],
  "title": "find_microdataArguments"
}

search_indicators

Rank official indicators; returns match evidence, retrieval health and source failures.

Parameters3

query	string	required
source_ids	any	optional
limit	integer	optional

Raw schema

{
  "type": "object",
  "properties": {
    "query": {
      "title": "Query",
      "type": "string"
    },
    "source_ids": {
      "anyOf": [
        {
          "items": {
            "type": "string"
          },
          "type": "array"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Source Ids"
    },
    "limit": {
      "default": 10,
      "title": "Limit",
      "type": "integer"
    }
  },
  "required": [
    "query"
  ],
  "title": "search_indicatorsArguments"
}

faostat_list_domains

List live FAOSTAT groups and domains available to build source-qualified series.

Parameters5

limit	integer	optional
cursor	integer	optional
group_code	any	optional
status	any	optional
include_archived	boolean	optional

Raw schema

{
  "type": "object",
  "properties": {
    "limit": {
      "default": 50,
      "title": "Limit",
      "type": "integer"
    },
    "cursor": {
      "default": 0,
      "title": "Cursor",
      "type": "integer"
    },
    "group_code": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Group Code"
    },
    "status": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Status"
    },
    "include_archived": {
      "default": false,
      "title": "Include Archived",
      "type": "boolean"
    }
  },
  "title": "faostat_list_domainsArguments"
}

faostat_search_dimension

Search a FAOSTAT domain's area, item, element, unit, or other definition table.

Parameters5

dataset	string	required
dimension	string	required
query	string	required
limit	integer	optional
cursor	integer	optional

Raw schema

{
  "type": "object",
  "properties": {
    "dataset": {
      "title": "Dataset",
      "type": "string"
    },
    "dimension": {
      "title": "Dimension",
      "type": "string"
    },
    "query": {
      "title": "Query",
      "type": "string"
    },
    "limit": {
      "default": 20,
      "title": "Limit",
      "type": "integer"
    },
    "cursor": {
      "default": 0,
      "title": "Cursor",
      "type": "integer"
    }
  },
  "required": [
    "dataset",
    "dimension",
    "query"
  ],
  "title": "faostat_search_dimensionArguments"
}

resolve_geographies

Resolve country names or codes to ISO 3166-1 alpha-3 codes such as GHA and KEN.

Parameters1

names_or_codes

array

required

Raw schema

{
  "type": "object",
  "properties": {
    "names_or_codes": {
      "items": {
        "type": "string"
      },
      "title": "Names Or Codes",
      "type": "array"
    }
  },
  "required": [
    "names_or_codes"
  ],
  "title": "resolve_geographiesArguments"
}

get_indicator_metadata

Retrieve authoritative metadata for a source-qualified series reference.

Parameters1

series_ref

string

required

Raw schema

{
  "type": "object",
  "properties": {
    "series_ref": {
      "title": "Series Ref",
      "type": "string"
    }
  },
  "required": [
    "series_ref"
  ],
  "title": "get_indicator_metadataArguments"
}

get_observations

Retrieve official observations while retaining metadata, citations and warnings.

Parameters6

series_ref	string	required
country_codes	array	required
start_year	any	optional
end_year	any	optional
latest_only	boolean	optional
include_original	boolean	optional

Raw schema

{
  "type": "object",
  "properties": {
    "series_ref": {
      "title": "Series Ref",
      "type": "string"
    },
    "country_codes": {
      "items": {
        "type": "string"
      },
      "title": "Country Codes",
      "type": "array"
    },
    "start_year": {
      "anyOf": [
        {
          "type": "integer"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Start Year"
    },
    "end_year": {
      "anyOf": [
        {
          "type": "integer"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "End Year"
    },
    "latest_only": {
      "default": false,
      "title": "Latest Only",
      "type": "boolean"
    },
    "include_original": {
      "default": false,
      "title": "Include Original",
      "type": "boolean"
    }
  },
  "required": [
    "series_ref",
    "country_codes"
  ],
  "title": "get_observationsArguments"
}

compare_observations

Retrieve series side by side and flag obvious metadata differences without merging them.

Parameters6

series_refs	array	required
country_codes	array	required
start_year	any	optional
end_year	any	optional
latest_only	boolean	optional
include_original	boolean	optional

Raw schema

{
  "type": "object",
  "properties": {
    "series_refs": {
      "items": {
        "type": "string"
      },
      "title": "Series Refs",
      "type": "array"
    },
    "country_codes": {
      "items": {
        "type": "string"
      },
      "title": "Country Codes",
      "type": "array"
    },
    "start_year": {
      "anyOf": [
        {
          "type": "integer"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Start Year"
    },
    "end_year": {
      "anyOf": [
        {
          "type": "integer"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "End Year"
    },
    "latest_only": {
      "default": false,
      "title": "Latest Only",
      "type": "boolean"
    },
    "include_original": {
      "default": false,
      "title": "Include Original",
      "type": "boolean"
    }
  },
  "required": [
    "series_refs",
    "country_codes"
  ],
  "title": "compare_observationsArguments"
}

README.md8 KBView on GitHub

Development Indicators MCP

A provenance-first Model Context Protocol gateway for official international-development indicators.

Hosted MCP endpoint: https://indicatorsmcp.impactengines.ai/mcp

The project aims to let AI agents discover and query authoritative indicators across institutions such as the World Bank, UN agencies, FAO, WHO, UNICEF, ILO and the DHS Program through one consistent interface. It preserves definitions, units, dimensions, source codes and citations rather than returning uncited prose.

Current milestone

The repository contains a working vertical slice:

remote-capable MCP server using Streamable HTTP, with stdio support for local clients;
source registry describing APIs, authentication and capabilities;
normalized indicator and observation schemas;
live World Bank, WHO GHO, UNICEF, FAOSTAT, ILOSTAT, IMF, UNSD SDG, UNESCO UIS, OECD and ADB adapters;
on-demand FAOSTAT authentication with no background token refresh;
dynamic FAOSTAT domain, country, item and element discovery;
weighted live catalogue search with aliases, match explanations, retrieval-health signals, bounded provider waits and a 15-minute query cache;
partial-failure comparisons, typed errors, native structured outputs and compact responses;
partial-success geography resolution with structured unresolved-country errors;
normalized ILOSTAT frequency labels and FAOSTAT dimension-ranking evidence;
tools to resolve country names, inspect metadata and retrieve observations;
unit tests for normalization and source behaviour.

This is a public beta, not a production statistical service. The hosted instance is provided for evaluation; you can also run or deploy your own copy.

MCP tools

list_sources(topic=None)
get_source_setup(source_id)
search_indicators(query, source_ids=None, limit=10)
get_indicator_metadata(series_ref)
get_observations(series_ref, country_codes, start_year=None, end_year=None, latest_only=False, include_original=False)
compare_observations(series_refs, country_codes, ...)
find_microdata(query, country=None)
faostat_list_domains(limit=50, cursor=0, group_code=None, status=None, include_archived=False)
faostat_search_dimension(dataset, dimension, query, limit=20, cursor=0)
resolve_geographies(names_or_codes)

Series references use the form source_id:series_code, for example world_bank:SP.POP.TOTL. Observation calls accept ISO 3166-1 alpha-3 codes such as GHA and KEN; use resolve_geographies when a prompt supplies country names. Mixed batches return both resolved and unresolved entries instead of failing the entire request.

Local development

powershell

py -3.11 -m venv .venv
.venv\Scripts\Activate.ps1
pip install -e ".[dev]"
pytest
development-data-mcp

For macOS or Linux, activate the environment with source .venv/bin/activate.

Run the live-source smoke benchmark with:

powershell

python -m benchmarks.run

The FAOSTAT check is skipped until FAOSTAT_USER and FAOSTAT_PASSWORD are configured; all public-source checks run without credentials.

The default transport is stdio. To run a hosted-style HTTP endpoint:

powershell

$env:MCP_TRANSPORT = "streamable-http"
$env:MCP_HOST = "127.0.0.1"
$env:MCP_PORT = "8000"
development-data-mcp

The MCP endpoint is then exposed at /mcp. Production deployment must add HTTPS, authentication, rate limiting and audit logging at the application or gateway layer.

Install in Codex

The hosted service uses Streamable HTTP:

powershell

codex mcp add development-indicators --url https://indicatorsmcp.impactengines.ai/mcp
codex mcp list

Restart Codex after adding it, then use /mcp to confirm the server and its tools are available. The same MCP configuration is shared by the Codex CLI, IDE extension and ChatGPT desktop app on the same Codex host.

Equivalent ~/.codex/config.toml configuration:

toml

[mcp_servers.development-indicators]
url = "https://indicatorsmcp.impactengines.ai/mcp"
startup_timeout_sec = 30
tool_timeout_sec = 180

Example test prompt: Using Development Indicators, find an official maize production series from FAOSTAT and retrieve 2020–2023 observations for Uganda and Kenya, preserving units, flags and citations.

Cloudflare deployment

The repository includes a Cloudflare Worker and Container configuration. It routes public HTTPS requests to the same tested Python image; the MCP endpoint remains /mcp. A production deployment should initially use its isolated workers.dev hostname, then attach a custom domain after client verification.

powershell

npm install
npm run deploy

To deploy under a different Worker name or hostname, edit name and routes in wrangler.jsonc. Remove the routes block if you only want a workers.dev endpoint. Authenticate Wrangler with your own Cloudflare account before running the deploy command; the repository contains no Impact Engines credentials.

Optional provider credentials can be added to your Worker without committing them:

powershell

npx wrangler secret put FAOSTAT_USER
npx wrangler secret put FAOSTAT_PASSWORD
npx wrangler secret put UN_POPULATION_TOKEN

See docs/deployment.md for the deployment architecture, verification checklist and non-Cloudflare Docker instructions.

Run with Docker

bash

docker build -t development-data-mcp .
docker run --rm -p 8000:8000 \
  -e MCP_TRANSPORT=streamable-http \
  -e MCP_HOST=0.0.0.0 \
  -e MCP_PORT=8000 \
  development-data-mcp

The endpoint will be available at http://localhost:8000/mcp. Put it behind HTTPS and suitable access controls before exposing it to the public internet.

Contributing

Issues and pull requests are welcome. Please run ruff check ., pytest, and npm run typecheck before submitting a change. See CONTRIBUTING.md for the full development workflow and SECURITY.md for private vulnerability reporting guidance.

Cloudflare Containers require a Workers paid plan. FAOSTAT credentials, when configured, must be stored with Wrangler secrets rather than committed.

Architecture

text

AI client
   |
Remote MCP gateway
   |
Metadata registry and source router
   |
Provider adapters (REST / SDMX / OData / specialist)
   |
Official publisher APIs

Only metadata and modest request caches should be stored locally at first. Observations are retrieved from official sources and returned in a common envelope while preserving the original source identifiers.

Planned source sequence

Active observation connectors: World Bank Indicators, WHO GHO, UNICEF SDMX, FAOSTAT, ILOSTAT, IMF DataMapper, UNSD SDG, UNESCO UIS, OECD SDMX and ADB SDMX. UN Population indicator discovery is active; its observation endpoint requires a portal-issued bearer token. DHS, MICS, IPUMS and World Bank Microdata Library remain catalogue-discovery integrations rather than observation APIs.

Safety and statistical integrity

Values are never invented or inferred by the MCP.
Similar indicators are not silently merged.
Provider codes and canonical URLs are retained.
Observed, survey-estimated, modelled and projected values must be labelled when metadata permits.
Microdata catalogue discovery does not imply permission to download restricted files.
Large results should be exported rather than placed directly in model context.

License

The software is released under the MIT License. Upstream data remain subject to each publisher's terms, licences and attribution requirements.

Install

Tools (10)

list_sourcesget_source_setupfind_microdatasearch_indicatorsfaostat_list_domainsfaostat_search_dimensionresolve_geographiesget_indicator_metadata

Remote endpoint

Streamable HTTP

Hosted server - connect over the network, no local install.

url

https://indicatorsmcp.impactengines.ai/mcp

Add to VS Code Add to Cursor

claude_desktop_config.json

json

{
  "mcpServers": {
    "development-indicators": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://indicatorsmcp.impactengines.ai/mcp"
      ]
    }
  }
}

Desktop config is stdio-only; this bridges via mcp-remote. Native remote: Settings > Connectors.

io.github.lbruce-wq/development-indicators — Model Context Protocol (MCP) Server

🛠️ Key Features

🚀 Use Cases

⚡ Developer Benefits

⚠️ Limitations

list_sources

get_source_setup

find_microdata

search_indicators

faostat_list_domains

faostat_search_dimension

resolve_geographies

get_indicator_metadata

get_observations

compare_observations

Development Indicators MCP

Current milestone

MCP tools

Local development

Install in Codex

Cloudflare deployment

Run with Docker

Contributing

Architecture

Planned source sequence

Safety and statistical integrity

License

Install

Remote endpoint

Related servers