Analytics Legends — SAP AI & Analytics MCP Server

List the deep-research studies (metadata only)

list_studies

Read-onlyIdempotent

List the Analytics Legends deep-research studies with their edition, as-of date, audience, word count and canonical URL. METADATA ONLY: study bodies are a paid deliverable, served by get_study on this same endpoint with an MCP Pass or Firm Pass key. Use this to tell a reader that a study exists and where to read it. ONE ROW IS ONE LANGUAGE EDITION, NOT ONE STUDY: each study is published in every language it has been translated into, so _meta.tranche_total_row_count counts editions and _meta.distinct_studies counts the works. _meta.available_languages gives the live per-language counts; each row carries its editions list. Pass lang to get one row per study.

Input Schema

Name	Required	Description
`lang`	No	ISO-639-1 language of the EDITION to list, e.g. en, fr or de — each study is published as one row per language. Omit it to see every edition of every study; the live list of languages actually present comes back as `_meta.available_languages` on every response. A well-formed code the corpus does not hold returns 0 rows.
`limit`	No	Max rows (hard cap 50).
`query`	No	Free-text filter, case-insensitive. EVERY word must appear in the record (substring per word, any order), so a natural-language phrase narrows the answer instead of having to match verbatim.
`cursor`	No	Opaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments; `null` means the last page. Changing a filter refuses the cursor.

Output Schema

Name	Required	Description	Default
`rows`	Yes
`tool`	Yes
`_meta`	No
`_attribution`	Yes
`result_count`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedSep 7, 2026

changedInput schema / properties / lang / description

Previous value: -"Language code, EN or FR."New value: +"ISO-639-1 language of the EDITION to list, e.g. en, fr or de — each study is published as one row per language. Omit it to see every edition of every study; the live list of languages actually present comes back as `_meta.available_languages` on every response. A well-formed code the corpus does not hold returns 0 rows."

addedOutput schema / properties / rows / items / properties / editions

Added value: +{
+  "items": {
+    "type": "string"
+  },
+  "type": [
+    "array",
+    "null"
+  ]
+}

addedOutput schema / properties / rows / items / properties / lang

Added value: +{
+  "type": [
+    "string",
+    "null"
+  ]
+}

Changed1 schema field changedAug 26, 2026

changedInput schema / properties / query / description

Previous value: -"Free-text filter, matched case-insensitively."New value: +"Free-text filter, case-insensitive. EVERY word must appear in the record (substring per word, any order), so a natural-language phrase narrows the answer instead of having to match verbatim."

Changed1 schema field changedAug 23, 2026

changedInput schema / properties / cursor / description

Previous value: -"Opaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments to read the next page; a null `next_cursor` means you have reached the end. It is bound to those filters and refused if they change — a cursor names a POSITION in one ordering, and applying it to another query would start the page in the wrong place."New value: +"Opaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments; `null` means the last page. Changing a filter refuses the cursor."

Changed1 schema field changedAug 10, 2026

addedInput schema / properties / cursor

Added value: +{
+  "description": "Opaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments to read the next page; a null `next_cursor` means you have reached the end. It is bound to those filters and refused if they change — a cursor names a POSITION in one ordering, and applying it to another query would start the page in the wrong place.",
+  "maxLength": 512,
+  "type": "string"
+}

Changed6 schema fields changedJul 31, 2026
- changedOutput schema / properties / rows / items / properties / access / type
```
Previous value: -"string"New value: +[
+  "string",
+  "null"
+]
```
- changedOutput schema / properties / rows / items / properties / as_of / type
```
Previous value: -"string"New value: +[
+  "string",
+  "null"
+]
```
- removedOutput schema / properties / rows / items / properties / citation_note
```
Removed value: -{
-  "type": "string"
-}
```
- changedOutput schema / properties / rows / items / properties / slug / type
```
Previous value: -"string"New value: +[
+  "string",
+  "null"
+]
```
- changedOutput schema / properties / rows / items / properties / title / type
```
Previous value: -"string"New value: +[
+  "string",
+  "null"
+]
```
- changedOutput schema / properties / rows / items / properties / word_count / type
```
Previous value: -"integer"New value: +[
+  "integer",
+  "null"
+]
```
Changed3 schema fields changedJul 31, 2026
- addedOutput schema / properties / rows / items / properties / citation_note
```
Added value: +{
+  "type": "string"
+}
```
- addedOutput schema / properties / rows / items / properties / citation_scope
```
Added value: +{
+  "enum": [
+    "record",
+    "section_hub"
+  ],
+  "type": "string"
+}
```
- addedOutput schema / properties / rows / items / properties / citation_url
```
Added value: +{
+  "type": "string"
+}
```
First observedJul 30, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds substantive context beyond them: content is paywalled and requires a pass key, the grain is one row per language edition rather than per study, and the `_meta` counters (`tranche_total_row_count`, `distinct_studies`, `available_languages`, `next_cursor`) are named. That is exactly the non-obvious behavior an agent would otherwise get wrong.

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

Conciseness4/5

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

Front-loaded with the resource and output fields, then scope, then the row-grain caveat, which is the highest-risk misconception. The all-caps warnings and the `_meta` enumeration make it denser than ideal, but nearly every clause carries actionable information rather than filler.

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 4-param, zero-required listing tool with an output schema and full annotation coverage, the description covers access model, row grain, language filtering, and pagination handoff. Nothing an agent needs in order to call it correctly or interpret the counts is missing.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3; the description still adds real meaning by explaining that `lang` collapses the edition-per-row grain into one row per study and that an unknown-but-valid code yields 0 rows, which the schema alone does not convey. It says less about `query` and `cursor` than the schema already does, so it does not fully earn a 5.

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?

States a specific verb and resource (list deep-research studies) plus exactly what fields each row carries (edition, as-of date, audience, word count, canonical URL), and explicitly separates itself from `get_study`, which serves the bodies. An agent can tell this is the catalog/metadata tool without opening any schema.

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?

Gives an explicit when-to-use ('tell a reader that a study exists and where to read it') and an explicit when-not/alternative ('study bodies are a paid deliverable, served by `get_study` on this same endpoint with an MCP Pass or Firm Pass key'). It also states the condition that changes the shape of the result ('Pass `lang` to get one row per study').

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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