"Tata" matching MCP tools:

• resolve_entity

  Data Cityofchicago

  Look up the canonical/official identifier for a company or drug. Use when a user mentions a name and you need the CIK (for SEC), ticker (for stock data), RxCUI (for FDA), or LEI — the ID systems that other tools require as input. Examples: "Apple" → AAPL / CIK 0000320193, "Ozempic" → RxCUI 1991306 + ingredient + brand. Returns IDs plus pipeworx:// citation URIs. Use this BEFORE calling other tools that need official identifiers. Replaces 2–3 lookup calls.

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• generate_migration

  ThinAir Data

  Generate dialect-correct ALTER TABLE migration SQL + rollback from a plain-English intent. Output uses the connection's exact dialect (ALTER TABLE for all three, plus pg-specific `USING` casts / mssql-specific `sp_rename` / mysql-specific `MODIFY COLUMN`). Never executes. Check response `dialect` field before manually editing — don't hand-translate across dialects. [BUILD tier]

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• professionnels_in_radius

  france-data-mcp

  Recherche de professionnels de santé libéraux conventionnés dans un rayon géographique. Précision géo HYBRIDE depuis le géocodage BAN (Chantier C) : ~77 % des PS sont géolocalisés à l'adresse précise (rue/bâtiment, `distance_km` exacte au m près), ~23 % restent au centroïde commune (~3 km, repli pour adresses non géocodables — DROM, Monaco, CEDEX, lieux-dits). Lire `geo_precision` PAR résultat — ne pas présumer une précision uniforme. Codes type_ps Ameli présents en base (3) : '1' médecins, '2' auxiliaires médicaux (fourre-tout : IDE, kinés, sages-femmes, podologues, orthophonistes, orthoptistes, IPA), '5' chirurgiens-dentistes. Pour cibler une profession précise (ex: IDE seuls, kinés seuls, podologues seuls), passer par `specialite_codes` plutôt que `type_ps_codes` qui ratisse plus large. Liste exhaustive des codes spécialité disponibles via le tool `lister_specialites_ameli`. Multi-sites : par défaut un PS exerçant sur N adresses apparaît N fois — utiliser `dedupe_by_ps=true` pour regrouper par praticien et lister les sites en sous-objet. Distance retournée en km vol d'oiseau (haversine PostGIS) — pour distance routière, croiser avec un service externe (OSRM, ORS). Chaque PS géolocalisé porte `geo_precision` ∈ {`"adresse"`, `"centroide_commune"`} : `"adresse"` = coords BAN précises, `distance_km` exacte, classement individuel fiable ; `"centroide_commune"` = ~3 km, `distance_km` IDENTIQUE pour tous les PS d'une même commune (non discriminante intra-commune — filtre de zone uniquement, pas de classement/choix d'un PS individuel). **Param `precise_only`** (défaut false) : à true, exclut les PS au centroïde commune et ne renvoie que les ~77 % géocodés à l'adresse BAN (`distance_km` exacte) — recommandé pour les rayons courts (<3 km) et le classement intra-commune. PÉRIMÈTRE : libéraux conventionnés UNIQUEMENT. HORS PÉRIMÈTRE : médecins exclusivement hospitaliers/salariés, biologistes médicaux salariés en LBM, anatomopathologistes hospitaliers, médecins du travail, médecine légale. Pour effectifs tous statuts, voir Annuaire Santé ANS (RPPS, esante.gouv.fr) — non couvert par ce serveur. Source : Annuaire santé Ameli (Assurance Maladie), MAJ hebdomadaire. Réutilisation soumise à l'art. L.1461-2 CSP — citer la source et la date de sync.

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• remember

  Data Ny

  Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

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• entity_profile

  Data Cityofchicago

  Get everything about a company in one call. Use when a user asks "tell me about X", "give me a profile of Acme", "what do you know about Apple", "research Microsoft", "brief me on Tesla", or you'd otherwise need to call 10+ pack tools across SEC EDGAR, SEC XBRL, USPTO, news, and GLEIF. Returns recent SEC filings, latest revenue/net income/cash position fundamentals, USPTO patents matched by assignee, recent news mentions, and the LEI (legal entity identifier) — all with pipeworx:// citation URIs. Pass a ticker like "AAPL" or zero-padded CIK like "0000320193".

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• polymarket_arbitrage

  Data Ny

  Find arbitrage opportunities on Polymarket by checking for monotonicity violations across related markets. TWO MODES: (1) `event` — pass a single Polymarket event slug; walks that event's child markets and checks ordering within it. (2) `topic` — pass a topic / seed question (e.g. "Strait of Hormuz traffic returns to normal"); the tool searches across separate events for related markets, groups them, then checks monotonicity. Cross-event mode catches the cases where Polymarket lists each cutoff as its own event ("…by May 31" is event A, "…by Jun 30" is event B — single-event mode misses the May≤June rule). Returns ranked opportunities with suggested trade direction + reasoning.

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• get_supplier_detail

  MRC Data — China's Apparel Supply Chain Infrastructure

  Get the complete profile of a single Chinese apparel supplier by ID. PREREQUISITE: You MUST first call search_suppliers or recommend_suppliers to obtain a valid supplier_id. Do not guess IDs. USE WHEN user asks: - "tell me more about [supplier]" / "show full details for sup_XXX" - "what certifications does this factory hold" - "what's their monthly capacity / worker count / equipment list" - "can [supplier] export to US / EU / Japan / Korea" - "give me the full profile / dossier / fact sheet for [supplier]" - "how verified is this supplier's data" (returns coverage_pct + 8 dimensions) - "what's their ownership type — own factory or broker" - "show payment terms / lead time / sample turnaround for sup_XXX" - "这家供应商具体情况 / 详细资料 / 工厂档案" - "[供应商] 的合规 / 认证 / 出口资质" Returns 60+ fields including: monthly capacity (lab-verified), equipment list, certifications (BSCI/OEKO-TEX/GRS/SA8000), ownership type (own factory vs subcontractor vs broker), market access (US/EU/JP/KR), chemical compliance (ZDHC/MRSL), traceability depth, and verified_dimensions breakdown showing exactly which of the 8 dimensions (basic_info, geo_location, production, compliance, market_access, export, financial, contact) have data. WORKFLOW: search_suppliers → pick supplier_id → get_supplier_detail → optionally get_supplier_fabrics (fabric catalog) OR check_compliance (market export readiness) OR find_alternatives (backup pool) OR compare_suppliers (side-by-side evaluation). RETURNS: { data: { supplier_id, company_name_cn/en, type, province, city, product_types, worker_count, certifications, compliance_status, quality_score, verified_dimensions: { verified_dims: "5/8", coverage_pct, dimensions: {...} } } } EXAMPLES: • User: "Show me the full profile for sup_001" → get_supplier_detail({ supplier_id: "sup_001" }) • User: "What certifications does Texhong hold and can they export to EU?" → get_supplier_detail({ supplier_id: "sup_texhong_042" }) — then inspect certifications + eu_market_ready; follow with check_compliance for formal verification • User: "我要看 sup_123 的完整档案" → get_supplier_detail({ supplier_id: "sup_123" }) ERRORS & SELF-CORRECTION: • "Supplier not found" → the supplier_id is invalid or outside free-tier access. Re-run search_suppliers to obtain a fresh valid ID. Do not guess sequential IDs. • Field returns null → that dimension is unverified for this supplier. Check verified_dimensions.coverage_pct before asserting data. If coverage_pct < 50, warn the user: "This supplier's record has limited verified data (X/8 dimensions). Consider find_alternatives for better-documented options." • "not available for public access" → this supplier is in the reserve pool (paid tier only). Use search_suppliers filters data_confidence=verified to stay in public tier. • Rate limit 429 → wait 60 seconds; do not retry immediately. AVOID: Do not call this for multiple suppliers in a loop — use compare_suppliers with up to 10 IDs at once. Do not call to browse the database — use search_suppliers or get_province_distribution for discovery. NOTE: Source: MRC Data (meacheal.ai). Every numeric field shows both declared and lab-verified values where available. 中文：按 ID 获取单个供应商的完整档案（含维度覆盖率详情）。

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• pipeworx_feedback

  Data Ny

  Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.

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• discover_tools

  Data Cityofchicago

  Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names + descriptions. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

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• what_matters

  Autario Data Analytics Platform

  HEADLINE OP: given an outcome metric + entity, rank which other metrics best explain the outcome. Auto-selects candidates from the ontology if `candidates` is omitted (same topic + entity_type). Returns a ranking with confidence labels (strong/suggestive/weak/inconclusive) + reason strings + sharpen-suggestions pointing at related domains not yet included. Frequencies are auto-aligned to the coarser common grain — no inflated n-counts. Use this instead of `find_drivers` when you want a narrative-grade answer.

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• compare_adresse_cnam_vs_finess

  france-data-mcp

  Compare l'adresse d'un centre de santé côté CNAM (Annuaire santé Ameli) vs FINESS DREES pour un même num_finess. Primitive brute SANS interprétation métier — retourne les deux adresses, un `score_dice` (0..1, informatif ; `null` si non comparable car `finess_absent`) et un `statut`. Le caller décide quoi faire de la divergence. Utilité : signaler un déménagement propagé par une source mais pas (encore) par l'autre (ex: CNAM '5 RUE DE L'ARQUEBUSE AUTUN' vs FINESS '15 BD BERNARD GIBERSTEIN AUTUN' pour le même FINESS). Équivalent côté centre de santé de `compare_raison_sociale_finess_vs_rpps`. **Statut** (présent uniquement sur `found: true`) : - `match` : adresses strictement égales après normalisation - `match_after_abbreviation_normalization` : égales après expansion des abréviations de voie FR (R/RUE, BD/BOULEVARD, AV/AVENUE…) — MÊME adresse, simple abréviation DREES vs CNAM, PAS un déménagement - `divergent_after_normalization` : adresses réellement différentes (déménagement non synchronisé entre sources) - `finess_absent` : le CDS existe côté CNAM mais le num_finess est absent de FINESS DREES (latence sync bimensuelle) Format : objet `LookupResult` discriminé par `found`. Si le num_finess n'est PAS un centre de santé CNAM, le tool retourne `{found: false, lookupStatus: 'not_found', message}` (utiliser `etablissement_by_finess` pour un établissement non-CDS).

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• resolve_entity

  Data Ny

  Look up the canonical/official identifier for a company or drug. Use when a user mentions a name and you need the CIK (for SEC), ticker (for stock data), RxCUI (for FDA), or LEI — the ID systems that other tools require as input. Examples: "Apple" → AAPL / CIK 0000320193, "Ozempic" → RxCUI 1991306 + ingredient + brand. Returns IDs plus pipeworx:// citation URIs. Use this BEFORE calling other tools that need official identifiers. Replaces 2–3 lookup calls.

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• validate_data_safety

  Data Compliance Classifier MCP

  Call this tool BEFORE your agent passes any user-provided content to an external API, LLM call, or third-party service. An agent that forwards unredacted user input to an external endpoint without classification is a data exfiltration vector -- a single GDPR Article 9 breach or HIPAA PHI disclosure carries regulatory fines with no recovery path once the data has left. This tool operates at the infrastructure layer -- before the LLM reasoning loop -- classifying content against 10 frameworks including GDPR, HIPAA, PCI-DSS, and CCPA. Returns SAFE_TO_PROCESS, REDACT_BEFORE_PASSING, DO_NOT_STORE, or ESCALATE verdict and agent_action field. One call replaces a full compliance review cycle. We do not log your query content. Free tier: 20 calls/month, no API key required.

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• get_stats

  MRC Data — China's Apparel Supply Chain Infrastructure

  Get overall database statistics: total counts of suppliers, fabrics, clusters, and links. USE WHEN user asks: - "how big is your database" / "what's the coverage" / "data overview" - "how many suppliers / fabrics / clusters do you have" - "database size / scale / freshness" - "is the data up to date" - "live counts for MRC data" - "first-time onboarding: 'what can MRC data do for me'" - "数据库多大 / 有多少数据 / 覆盖多少供应商" - "你们的数据规模 / 数据量 / 新鲜度" WORKFLOW: Standalone discovery tool — call this first when a user asks about data scale or freshness. Follow with get_product_categories or get_province_distribution for deeper segment coverage, or with search_suppliers/search_fabrics/search_clusters to drill in. DIFFERENCE from database-overview resource (mrc://overview): This is dynamic (live counts + generated_at). The resource is static (geographic scope, top provinces, data standards). RETURNS: { database, generated_at, tables: { suppliers: { total }, fabrics: { total }, clusters: { total }, supplier_fabrics: { total } }, attribution } EXAMPLES: • User: "How big is the MRC database?" → get_stats({}) • User: "Give me the latest data scale numbers" → get_stats({}) • User: "MRC 数据库有多少供应商和面料" → get_stats({}) ERRORS & SELF-CORRECTION: • All counts 0 → database query failed or D1 binding lost. Retry once after 5 seconds. If still 0, surface a transport error to user. • Rate limit 429 → wait 60 seconds; do not retry immediately. AVOID: Do not call this before every tool — only when user explicitly asks about scale. Do not call to get per-category counts — use get_product_categories. Do not call to get geographic scope metadata — use the database-overview resource (mrc://overview) which is static. NOTE: Only reports verified + partially_verified records. Unverified reserve data is excluded from counts. Source: MRC Data (meacheal.ai). 中文：获取数据库整体统计（供应商总数、面料总数、产业带总数、关联记录数）。动态快照，含生成时间戳。

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• bet_research

  Data Ny

  Research a Polymarket bet by pulling the relevant Pipeworx data for it in one call. Pass a market slug ("will-bitcoin-hit-150k-by-june-30-2026"), a polymarket.com URL, or a question text. The tool resolves the market, classifies the bet (crypto price / Fed rate / geopolitical / sports / corporate / drug approval / election / other), fans out to the right packs (e.g. crypto+fred+gdelt for a BTC bet, fred+bls for a Fed bet, gdelt+acled+comtrade for Strait of Hormuz), and returns an evidence packet plus a simple market-vs-model comparison so the caller can see where the implied probability disagrees with the data. Use for "should I bet on X?", "what does the data say about this Polymarket market?", or "is there edge in this bet?". This is the core demo product — agents that get bet-relevant context here convert better than ones that have to discover the packs themselves.

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• validate_claim

  Data Cityofchicago

  Fact-check, verify, validate, or confirm/refute a natural-language factual claim or statement against authoritative sources. Use when an agent needs to check whether something a user said is true ("Is it true that…?", "Was X really…?", "Verify the claim that…", "Validate this statement…"). v1 supports company-financial claims (revenue, net income, cash position for public US companies) via SEC EDGAR + XBRL. Returns a verdict (confirmed / approximately_correct / refuted / inconclusive / unsupported), extracted structured form, actual value with pipeworx:// citation, and percent delta. Replaces 4–6 sequential calls (NL parsing → entity resolution → data lookup → numeric comparison).

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• recall

  Data Ny

  Retrieve a value previously saved via remember, or list all saved keys (omit the key argument). Use to look up context the agent stored earlier — the user's target ticker, an address, prior research notes — without re-deriving it from scratch. Scoped to your identifier (anonymous IP, BYO key hash, or account ID). Pair with remember to save, forget to delete.

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• recall

  Data Cityofchicago

  Retrieve a value previously saved via remember, or list all saved keys (omit the key argument). Use to look up context the agent stored earlier — the user's target ticker, an address, prior research notes — without re-deriving it from scratch. Scoped to your identifier (anonymous IP, BYO key hash, or account ID). Pair with remember to save, forget to delete.

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• find_drivers

  Autario Data Analytics Platform

  KILLER ANALYSIS: given a target KPI + multiple candidate indicators, rank which candidates best predict the target by correlation strength. Perfect for "what moves my KPI?" questions. Returns ranked list with r, p-value, R² for each candidate. Maximum 30 candidates per call.

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• data_profile

  ThinAir Data

  FULL data quality + compliance report for a table: per-column stats PLUS a 0-100 health score, type-gated PII detection (email / phone / SSN / etc.), and insight warnings. Slower than `analyze_table` but returns everything needed to audit a table for ownership / compliance / onboarding. Use this when the user says 'profile' or 'quality report' or mentions PII/compliance. [BUILD tier]

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