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SidneyBissoli

UNESCO Institute for Statistics (UIS) MCP Server

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
API_KEYNoOptional bearer token for authenticating requests to the MCP endpoint.

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}
resources
{
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
uis_search_indicatorsA

Search the UNESCO Institute for Statistics catalogue of ~5,000 indicators — education, science/R&D, culture and communication — by keywords in the name or code, optionally filtered by theme. All terms must match (AND, case-insensitive), so start with 2–3 words and drop terms if you get 0 results. Everyday and US wording is resolved to the UIS's own (enrollment→enrolment, spending→expenditure, preschool→pre-primary, university→tertiary, graduation→completion, girls/boys→female/male); when that happens the response says so in vocabulary_notes. Returns indicator codes to use with uis_get_data, plus each indicator's data availability (years, record count). Searches the catalogue only — it does not return statistical values (use uis_get_data); ILO labour statistics live in the sibling ILOSTAT MCP server.

uis_list_geo_unitsA

Valid geographic codes for uis_get_data: 462 geo units — countries (NATIONAL, ISO alpha-3 codes like BRA) and regional aggregates (REGIONAL). Filter by name/code and type. Does not return statistical values; these codes apply only to uis_get_data, not to other statistical servers.

uis_get_dataA

Statistical records from the UNESCO Institute for Statistics Data API, filtered by indicator codes (from uis_search_indicators, up to 25), geo unit codes (from uis_list_geo_units) and year range. Set include_footnotes for per-record source notes. Returns raw UIS records only — it does not aggregate, convert or otherwise transform values; ILO labour statistics live in the sibling ILOSTAT MCP server. Broad queries are rejected with the record count — narrow by geo unit or years. A code that does not exist is an error carrying the UIS API's own wording, never an empty result: zero rows means the codes are real and the selection has no data, and the hint then relays what the UIS reported (including the indicator's available year range). When only SOME of the requested codes exist, the matching rows are returned with warnings naming the rest. Values are those of the release named in data_vintage: a new UIS release can revise past years, and qualifier/magnitude on a record flag how the value was obtained (e.g. UIS estimate).

searchA

Searches the UNESCO UIS statistics (≈5,000 indicators: education — enrolment, completion, literacy, teachers, spending, SDG 4 —, science/R&D (SDG 9.5), culture (SDG 11.4) and demographic context) catalog and returns up to 10 matching documents as { id, title, url }, ordered by relevance (an empty list means nothing matched).

This tool exists for the OpenAI Deep Research contract: ChatGPT deep research, company knowledge and research workflows over the Responses API require exactly the tools search and fetch. Pass one of the returned ids to fetch to read the document. For direct questions and for data (values, series, rankings) prefer the uis_* tools, which return the actual data with provenance — this is a catalog index, not a data query.

Query: natural language or keywords, Portuguese or English; accents and case are ignored.

Behavior: read-only and idempotent — the catalog comes from the public source and is cached in memory.

fetchA

Returns the full document for an id obtained from search, as { id, title, text, url, metadata }: text is the readable content (Markdown) and url the canonical public page to cite.

Companion of search in the OpenAI Deep Research contract, over the UNESCO UIS statistics (≈5,000 indicators: education — enrolment, completion, literacy, teachers, spending, SDG 4 —, science/R&D (SDG 9.5), culture (SDG 11.4) and demographic context) catalog. Only ids returned by search are valid; an unknown id returns an error. The uis_* tools remain the tools for data queries.

Behavior: read-only and idempotent — a live GET against the public source when the document needs it.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription
uis-guideHow to query the UNESCO UIS with this server: tool workflow, code conventions (indicator code families and suffixes, ISO alpha-3 geo units, themes), limits and reporting rules. Read once per session to save discovery calls.
uis-key-indicatorsVerified indicator codes for the most common questions — completion, out-of-school, enrolment, literacy, learning proficiency, education spending, R&D (SDG 9.5), heritage spending (SDG 11.4) and population — usable directly in uis_get_data.
uis-provenanceMeaning of every provenance field returned with the data (source_url, data_vintage, retrieved_at, retrieval, license, citation, derived) and how to cite the UIS correctly, including what CC BY-SA ShareAlike requires downstream.

TDQS

A4.4/5.0

Scored across 5 tools

Disambiguation4/5

The three uis_* tools are clearly separated by purpose (geo codes vs. indicator discovery vs. data retrieval). The only overlap risk is between uis_search_indicators and the bare `search` tool, both of which search the UIS catalogue, but the descriptions explicitly distinguish them (indicator codes for data queries vs. a document catalog index for the Deep Research contract).

Naming Consistency4/5

Three tools follow a clean uis_verb_noun pattern (uis_list_geo_units, uis_search_indicators, uis_get_data), while `search` and `fetch` are bare verbs. The deviation is deliberate (OpenAI Deep Research contract requires exactly those names) and still readable, so it is a minor inconsistency rather than chaos.

Tool Count5/5

Five tools is well-scoped for a statistical data server: geographic lookup, indicator discovery, data retrieval, plus a document search/fetch pair. Each tool earns its place with no redundancy.

Completeness4/5

The surface covers the full workflow: resolve geo units, discover indicators, fetch data with provenance, and read catalog documents. It lacks dedicated metadata/vintage or aggregation helpers, but those are explicitly out of scope and agents can work around them.

Maintenance

ActivityActive
ResponsivenessNo issues