Analytics Legends — SAP Analytics Intelligence

{
  "id": "aix_80b5e1bfa0",
  "name": "Analytics Legends — SAP Analytics Intelligence",
  "operator": "(unclaimed - source: registry-official · publisher: ai.analyticslegends)",
  "description": "AI agent for SAP analytics: firms, day rates, contract radar, news, concepts, studies",
  "depth": 2,
  "status": "unclaimed",
  "last_crawled": "2026-09-24",
  "missing_fields": [
    "pricing",
    "operator.identity"
  ],
  "skills": [
    "data-enrichment",
    "sql-database",
    "translation-qa"
  ],
  "protocols": {
    "mcp": "https://analyticslegends.ai/mcp",
    "a2a": null
  },
  "pricing": null,
  "regions": [
    "global"
  ],
  "languages": [
    "en"
  ],
  "reputation": {
    "tasks_completed": null,
    "dispute_rate": null,
    "p95_latency_ms": 1914,
    "uptime_30d": 1,
    "onchain_volume_30d_usd": null
  },
  "aix_score": 48,
  "verification": {
    "identity": "none",
    "health": "probe/24h",
    "pricing": "unknown",
    "last_check": "2026-09-24T23:01:06.236Z"
  },
  "pricing_model": "unknown",
  "links": [
    {
      "label": "homepage",
      "url": "https://analyticslegends.ai/"
    },
    {
      "label": "repository",
      "url": "https://github.com/analyticslegends/analytics-legends-mcp"
    }
  ],
  "avatar": "https://github.com/analyticslegends.png?size=160",
  "socials": [
    {
      "label": "github",
      "url": "https://github.com/analyticslegends"
    }
  ],
  "profile": {
    "mcp_server": "analytics-legends",
    "mcp_version": "1.0.6",
    "tool_count": 20,
    "tools": [
      {
        "name": "search_firms",
        "description": "Search the published Analytics Legends directory of SAP analytics service providers — placement agencies, Big-4 and ESN practices, SAP vendors, platforms and community groups — by country, kind, declared SAP module and free text. Returns name, HQ country/city, website, careers URL and a one-line editorial claim. SAP END-CUSTOMER companies are NOT in this directory: they are a separate paid dataset, excluded here by the `is_client` FLAG — not by the `client_enterprise` kind code. The two are different columns, and where a row's flag and its kind label disagree in the SSOT it is the flag that de"
      },
      {
        "name": "count_firms_by",
        "description": "Answer a COUNTING question about the published firm directory in one call: how many organisations per country, per kind, per declared SAP module, or per SAP signal band — with the same `country`/`kind`/`module`/`query` filters `search_firms` takes, so you can count a slice as easily as the whole. Use this instead of paging `search_firms` and tallying rows: the directory holds thousands of organisations, and reading them all to produce a table of counts costs hundreds of calls and megabytes of rows for numbers Postgres computes in one scan. Every bucket is a value the directory actually stores;"
      },
      {
        "name": "get_firm",
        "description": "Fetch one organisation from the published directory by its database slug (`rows[].slug` from search_firms, verbatim). Returns the same public fields plus `partnerships_declared`, the count of partnerships this directory records for the firm — 0 on ~97 % of rows (re-measured 2026-08-14 on the published tranche: 96,8 %), meaning none declared here, never that the firm has no partners. Does not return the paid firm-intelligence profile, contacts, or any person."
      },
      {
        "name": "list_firm_kinds",
        "description": "Breakdown of the published firm directory by organisation kind, with a live row count per kind. Use this before search_firms to know what the population actually is instead of guessing."
      },
      {
        "name": "list_freelance_platforms",
        "description": "The subset of the published directory where a consultant can CREATE A PROFILE — freelance marketplaces, job boards with candidate profiles, talent platforms and expert networks — each with its signup URL, an editorial confidence grade and the date it was assessed. This answers the entering-contractor's first practical question ('where do I register?') in one call. Everything here is also in search_firms — this tool adds the platform fields and the filter, never a wider population. `signup_url` is the platform's own page: it was verified on `assessed_at`, and a platform absent here is not prove"
      },
      {
        "name": "find_opportunities",
        "description": "Search every SAP contract and permanent-role posting Analytics Legends publishes to an ANONYMOUS visitor — the same population a human browses on /opportunities/, where each posting has its own prerendered page. It merges the platform's TWO public legs, which are near-disjoint (measured 2026-07-30: 1 row in common): (a) the PROMOTED feed (`public.public_opportunities`) — general SAP work (FI/CO, SD, EWM, MDG, BTP, ABAP), all German cities, dated (posted_at is populated on EVERY active row of that leg — an invariant held since 2026-07-31, not a snapshot). 🔴 THIS LEG CHANGED SHAPE ON 2026-08-28"
      },
      {
        "name": "search_news",
        "description": "Search the Analytics Legends market-news corpus. It is watched FOR SAP analytics (Datasphere, Business Data Cloud, SAC, BW/4HANA, Databricks, the 2027/2030 maintenance window), but it is NOT an all-SAP corpus: measured 2026-07-30, ~84 % of active rows sit in the `AI` category and are general enterprise-AI trade press (cloud platforms, model releases, funding rounds) with no SAP content at all. An UNFILTERED call therefore returns mostly non-SAP items — pass `query` or `category` when the question is about SAP, and never present an unfiltered page as 'the SAP analytics news'. Say what you actua"
      },
      {
        "name": "search_concepts",
        "description": "Search the SAP analytics concept encyclopaedia — the vocabulary of the stack, written for practitioners. Returns slug, title, category, level, tags and the editor's summary. `level` is GRADED on every active row since 2026-09-18 (the CHECK constraint accepted only the legacy vocabulary OR NULL, so the loader wrote NULL rather than fail; 108 of 330 were blank). A null, if one ever returns, means 'not graded', never 'Beginner'. These are the same fields `get_concept` returns for ONE slug. The card BODY (cheat sheet, glossary, pro tip and the four analysis tables) is Consultant-tier: call `get_co"
      },
      {
        "name": "get_concept",
        "description": "Fetch one concept entry by slug: title, category, level, tags and the editor's summary. Written by a named human editor, not generated. `level` is GRADED on every active row since 2026-09-18 (the CHECK constraint accepted only the legacy vocabulary OR NULL, so the loader wrote NULL rather than fail; 108 of 330 were blank). A null, if one ever returns, means 'not graded', never 'Beginner'. The card body, cheat sheet, glossary, pro tip and the four analysis tables are subscriber content and are NOT returned. Why-it-matters and key points are not returned here either, but they ARE published in fu"
      },
      {
        "name": "list_studies",
        "description": "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 Consultant-tier deliverable, served by `get_study` on this same endpoint with a subscriber 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 cou"
      },
      {
        "name": "get_day_rate_benchmark",
        "description": "The PUBLIC day-rate aggregate for SAP analytics freelance work: min/max daily rate by country, specialisation and seniority — `daily_rate_min` / `daily_rate_max` (plus `daily_rate_median`, `daily_rate_p10`, `daily_rate_p90` when the source publishes them), every amount in the row's own `currency` — with source, source date, confidence and the sample the source states. This is the free aggregate published at analyticslegends.ai/api/market-rates.json, and it is SMALL — a few dozen rows at most, every one of them a secondary source (a published market study or a job-board scan), and `sample_size`"
      },
      {
        "name": "list_sap_modules",
        "description": "The canonical SAP module/product taxonomy Analytics Legends classifies against (codes and EN/FR labels by category). Use it to normalise a user's loose product wording — 'SAC', 'Analytics Cloud', 'Datasphere' — onto the codes the other tools filter on."
      },
      {
        "name": "find_academy_modules",
        "description": "Search the Analytics Legends Academy — the written training modules on SAP Datasphere, Business Data Cloud, SAP Analytics Cloud, BW/4HANA and Databricks — by track, level and free text. `_meta.tranche_total_row_count` carries the live catalogue size on every call; it is the only count to quote. Returns the catalogue entry: id, slug, EN/FR title, track, level, duration in minutes, tags and the editor's summary. DO NOT CONFUSE IT WITH `list_sap_modules`, which serves a different population under the same word: that one is the 40-row PRODUCT taxonomy (codes such as SAC, DATASPHERE) used to normal"
      },
      {
        "name": "query_knowledge_graph",
        "description": "The RELATIONS between the platform's teaching objects — which Academy module teaches which concept, which study covers which module, what a concept relates to. THIS IS THE ONLY TOOL ON THIS SERVER THAT SERVES EDGES; the others serve rows. Ask it what connects to what, not what exists. SCOPE, AND IT IS NARROWER THAN 'the knowledge graph': it carries four node types — `concept`, `module`, `study`, `vendor` — and every edge whose BOTH endpoints are one of them. The whole graph holds twelve node types; the eight it does not carry are each either served by their own tool or named as not served at a"
      },
      {
        "name": "get_concept_card",
        "description": "The FULL encyclopaedia card for one concept — body, cheat sheet, glossary, pro tip, and the four analysis tables (decision table, peer comparison, named pitfalls, performance facts), EN, FR and DE, plus why-it-matters and key points (those two are also published free on the concept page; here they come structured, in three languages, in the same payload) — the corpus the €29.90 Consultant Pass sells. On THIS endpoint the machine-access subscription is the MCP Pass (€39.90/month, analyticslegends.ai/pricing/), which opens the ENTIRE paid tranche from one key; the €29.90 Consultant Pass is its w"
      },
      {
        "name": "get_study",
        "description": "Read one Analytics Legends study BODY — the paid text behind list_studies' metadata. Requires a subscriber API key, Consultant tier or above. Bodies run to 38k words and exceed the 256 KiB response ceiling, so this tool serves STRUCTURE first: called without `section` it returns the section list and the introduction; pass `section` (a heading from that list, matched case-insensitively) to read one section. Find slugs and languages with list_studies."
      },
      {
        "name": "get_academy_module",
        "description": "Read one Academy training module in full — body, learning objectives and summary, EN, FR and DE — the written course corpus the €29.90 Consultant Pass sells. On THIS endpoint the machine-access subscription is the MCP Pass (€39.90/month, analyticslegends.ai/pricing/), which opens the ENTIRE paid tranche from one key; the €29.90 Consultant Pass is its web-subscriber equivalent and opens the same tier floor here. Requires a subscriber API key (Authorization: Bearer alk_…), Consultant tier or above; without one this tool refuses and `find_academy_modules` keeps serving the catalogue. Takes the mo"
      },
      {
        "name": "find_sap_clients",
        "description": "Search the SAP END-CUSTOMER corpus — the companies that RUN SAP, not the firms that sell services (those are search_firms). This is the paid Legend+ dataset locked away from the public surface on 2026-07-08; it requires a subscriber API key, Legend tier or above. Verification status is SERVED, never silently filtered: `sap_client_verification_status` and `status` are columns on every row ('verified' on ~550 of ~21k rows), and you decide what standard of proof your answer needs. `product` filters on the detected-adoption flags every profile already carries (the `uses_*` columns get_sap_client_p"
      },
      {
        "name": "get_sap_client_profile",
        "description": "The full profile of one SAP end-customer — SAP footprint (products in use, modules known), analytics solutions, identity and evidence fields. Requires a subscriber API key, Legend tier or above. `id` comes verbatim from find_sap_clients.rows[].id."
      },
      {
        "name": "get_firm_intel",
        "description": "The paid intelligence profile of a services firm — SAP practice size and partner level, delivery flags per product, typical day rate and seniority, notable clients, analytics practice summary, and a LinkedIn company URL (present on ~71% of the corpus, re-measured 2026-09-05 on 9,104 profiles — it read ~39% from 2026-08-10 to 2026-09-05, i.e. a third of the corpus below the truth, because an enrichment pass filled the column and no reader of this sentence was told — glassdoor_rating, glassdoor_reviews_count and linkedin_followers are null on the entire corpus as of 2026-08-10, absence here is a"
      }
    ],
    "profiled_at": "2026-09-24T23:01:06.236Z"
  },
  "unreachable": false
}