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faostat-mcp-server

by io.github.cyanheads

faostat-mcp-server: resolve codes

faostat_resolve_codes
Read-onlyIdempotent

Resolve human terms to the opaque integer codes faostat_query_observations needs, within a dimension: areas (countries/regions), items (commodities), or elements (metrics like production, yield, import quantity). Pass query for fuzzy full-text matching ("maize" → item 56), name_contains for a substring filter, or code for an exact-code lookup; omit all three to list the whole dimension. Item and element results are scoped to the requested domain — only codes present in that domain's cube are returned, so a resolved code is always queryable there (areas are shared across domains). Page large listings with offset + limit: when the response reports truncated, pass the returned nextOffset to fetch the next page. Every area match is flagged country or aggregate — aggregates (World, continents, economic groupings — codes ≥ 5000 plus a few curated sub-threshold roll-ups such as China=351, which sums mainland + Taiwan + Hong Kong + Macao) double-count if summed with their member countries, so resolve before querying and exclude aggregates unless you want the regional roll-up.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeNoExact code lookup. Takes precedence over `query`/`name_contains` when provided.
limitNoMaximum matches to return (max 200).
queryNoFull-text search term, FTS5-matched against the dimension labels with prefix matching (e.g. "wheat", "import quantity"). Relevance-ranked.
domainYesFAOSTAT domain code (e.g. "QCL"). Item and element resolution is scoped to the codes present in this domain's data; area code lists are shared across all indexed domains.
offsetNoZero-based pagination offset into the match set. When the response reports truncated, pass the returned nextOffset here to fetch the next page. Ignored for exact-code lookups (always single-page).
dimensionYesWhich dimension to resolve: "area" (countries/regions), "item" (commodities), or "element" (metrics).
name_containsNoCase-insensitive substring filter over the label. Used only when `query` is omitted.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent when the call failed. Absent on success.
domainNoThe domain code echoed back.
noticeNoGuidance when nothing matched, more pages remain, or the dimension is not yet indexed.
matchesNoMatching codes, relevance-ranked for query mode, else by code.
dimensionNoThe dimension resolved.
truncatedNoTrue when more matches remain beyond the returned page — fetch them with nextOffset.
nextOffsetNoOffset to pass on the next call to fetch the following page. Present only when truncated is true; absent on the last page and for exact-code lookups.
totalMatchesNoTotal matches in this domain before the result cap.

TDQS

A5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds substantial behavior beyond annotations: domain scoping of item/element results, the 'country' vs 'aggregate' flag, the ≥5000 code heuristic (plus curated exceptions like China=351), double-counting risk, and the truncated/nextOffset pagination contract. It never contradicts readOnlyHint or idempotentHint—it enriches them.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but every sentence contributes: purpose, three matching modes, domain scoping, pagination mechanics, aggregate warning with specific examples. It is front-loaded with the core purpose and ends with the critical usage caveat. No filler; each clause earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 7-parameter tool with an output schema and annotations, the description leaves nothing ambiguous: it covers all parameter relationships, pagination, domain scoping, and a major data-quality pitfall. Given the existence of an output schema, the lack of return-value details is appropriate. It is fully complete for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 100% schema coverage, the description adds real meaning: it gives a concrete example ('maize' → item 56), clarifies precedence relationships among query/name_contains/code, states that code takes precedence and name_contains is used only when query is omitted, and explains offset/limit behavior. This is more than the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear verb and resource ('Resolve human terms to the opaque integer codes... within a dimension') and enumerates the three dimensions (areas, items, elements). It explicitly distinguishes itself from faostat_query_observations by saying these codes are what that tool needs, so agents can tell them apart without inspecting schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly says when to use this tool ('resolve before querying') and what to exclude (aggregates unless you want the regional roll-up). It also details the three matching modes and when each applies, plus pagination instructions with nextOffset. This is among the best guidance seen, covering both when and how.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: discovery (list_domains), code resolution (resolve_codes), raw data query (query_observations), high-level profile assembly (commodity_profile), and dataframe management (describe/query). The composite profile tool overlaps slightly with query_observations, but its description clearly positions it as a convenience wrapper, eliminating ambiguity.

Naming Consistency4/5

All tools share the faostat_ prefix, and most use verb_noun structure (list_domains, query_observations, resolve_codes, dataframe_describe, dataframe_query). The exception is commodity_profile, which is a noun_phrase rather than verb-first, though it is still descriptive and follows the overall underscore convention. This minor deviation keeps the set mostly consistent.

Tool Count5/5

With 6 tools, the server is well-scoped for its purpose: it covers the essential workflow of discovering domains, resolving codes, querying data, and analyzing results via dataframes. Each tool has a clear role, and the count is appropriate for a focused statistical data server without excess or deficiency.

Completeness5/5

The tool surface covers the full data retrieval lifecycle: domain discovery, code resolution, raw data extraction, and flexible post-query analysis (including a high-level commodity profile shortcut). The descriptions handle edge cases like aggregation exclusion and flag validation, and no obvious gaps exist for a read-only FAOSTAT querying server.

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