The MCP tool directory.

List product types in a schema. ProductTypes are the flat product classification within a schema (NOT to be confused with categories, which are sales navigation). Response: { productTypes: [{ id, schemaId, code, labels, defaultTraitIds, parentCode, level, isActive, productCount }] }. Errors: { error: { code: 'not_found', ... } }.

Create a tenant-owned PIM schema, or return the existing one if `name` already exists for this tenant. Only Master and Recipient kinds are creatable via MCP — Standard (eClass/ETIM/UNSPSC) and Connector schemas are platform-managed. Response: { schema: {...}, created: bool }. Errors: { error: { code: 'bad_input', ... } }.

Get a PIM schema by id, with productTypes, traits, attributeDefinitions, and channels embedded. Use the optional `fields` param to limit the response to specific top-level keys when the full payload is too large. Allowed `fields` values: schema, productTypes, traits, attributeDefinitions, channels. Response: { schema?: {...}, productTypes?: [...], traits?: [...], attributeDefinitions?: [...], channels?: [...] }. Errors: { error: { code: 'not_found' | 'forbidden', ... } }.

List PIM schemas in the current tenant. By default returns only tenant-owned, editable schemas (Master + Recipient). To inspect Import (file-import) or Standard (eClass/ETIM/UNSPSC) or Connector schemas, pass `kind` explicitly. Response: { schemas: [{ id, name, kind, contentLanguage, productTypeCount, traitCount, categoryCount, attributeDefinitionCount, isReadOnly, updatedAt }] }. Errors: { error: { code: 'bad_input', ... } }.

Set the schema's default LLM role/context (the system-prompt-style preamble used in AI ops). Pass null to clear. Response: { schemaId, defaultAiRole }. Errors: { error: { code: 'not_found' | 'bad_input', ... } }.

Set the schema's default channel codes — the codes auto-assigned to new products in this schema. This replaces the existing list. Pass [] to clear. Response: { schemaId, defaultChannelCodes }. Errors: { error: { code: 'not_found', ... } }.

Set the schema's product-number template. C = category code character, N = sequential digit, any other character = literal. Example: 'CCCC-NNNNNNNN' renders 'PUMP-00000001'. Pass null to clear. Response: { schemaId, productNumberTemplate }. Errors: { error: { code: 'not_found', ... } }.

Bind one or more attribute definitions to a trait by setting their `traitId`. Each attribute definition in the list has its `traitId` updated to the given trait. Idempotent — already-bound definitions are no-ops. Definitions in other schemas or other tenants are skipped with a reason. Response: { traitId, attributeDefinitionIds, bound: count, skipped: [{ id, reason }] }. Errors: { error: { code: 'not_found', ... } }.

Unbind attribute definitions from a trait — clears their `traitId` only when it equals the given trait. Definitions bound to other traits are left untouched. Idempotent. Response: { traitId, attributeDefinitionIds, unbound: count, skipped: [{ id, reason }] }. Errors: { error: { code: 'not_found', ... } }.

Create a trait in a schema, or return the existing one if `code` already exists. Traits are reusable groups of attribute definitions; products opt in to traits to gain their attributes. To bind attribute definitions to the trait after creation, use pim.traits.attributes.add (or set `traitId` directly when creating attribute definitions). Response: { trait: {...}, created: bool }. Errors: { error: { code: 'not_found' | 'bad_input', ... } }.

Get a trait by id, with its trait-scoped attribute definitions resolved. Response: { trait: {...}, attributeDefinitions: [...] }. Errors: { error: { code: 'not_found', ... } }.

List traits in a schema. Traits are reusable groups of attribute definitions; products opt in to traits to gain their attributes. Response: { traits: [{ id, schemaId, code, labels, sortOrder, isActive }] }. Errors: { error: { code: 'not_found', ... } }.

Orquestador de Enjambres Multi-Agente — /api/ping endpoint. Fee: $0.01 USDC via x402.

Retrieve details and videos from a specific YouTube playlist

Get information about a YouTube playlist

Get videos in a YouTube playlist

Generate a Portal Link scoped to an Organization.

Compute close rate across all products based on CRM conversion states.

Explore Infobip Documentation; Use semantic search to explore the Infobip documentation hub, a comprehensive collection of product documentation, practical use cases, and general platform information designed to help both new and advanced users find resources and inspiration for interacting with end-users.

Search court precedents (판례 목록 조회). Search Korean court precedents from Supreme Court and lower courts. Args: query: Search keyword (default "*" for all) display: Number of results per page (max 100, default 20) page: Page number (1-based, default 1) oc: Optional OC override (defaults to env var) type: Response format - "JSON" (default), "XML", or "HTML" search: Search type (1=case name, 2=full text, default 1) sort: Sort order - "lasc"|"ldes"|"dasc"|"ddes"|"nasc"|"ndes" org: Court type code (400201=Supreme Court, 400202=lower courts) curt: Court name (대법원, 서울고등법원, etc.) jo: Referenced law name (형법, 민법, etc.) gana: Dictionary search (ga, na, da, ...) date: Decision date (YYYYMMDD) prnc_yd: Decision date range (YYYYMMDD~YYYYMMDD) nb: Case number (comma-separated for multiple) dat_src_nm: Data source name (국세법령정보시스템, 근로복지공단산재판례, 대법원) pop_yn: Popup flag ("Y" or "N") Returns: Search results with precedent list or error Examples: Search for precedents mentioning "담보권": >>> prec_search(query="담보권", display=10) Search Supreme Court precedents: >>> prec_search(query="담보권", curt="대법원")

Retrieve court precedent full text (판례 본문 조회). Args: id: Precedent sequence number (판례일련번호) lm: Precedent name (optional) sections: Response detail level: - "summary": Returns 판시사항, 판결요지, 참조조문, 참조판례 only (~5KB). Excludes 판례내용 (full judgment text, often 15-25KB). **Recommended for PlayMCP** to stay under 20KB limit. - "full" or None: Returns everything including 판례내용 (default). oc: Optional OC override type: Response format - "JSON" (default), "XML", or "HTML" Returns: Full precedent text with details or error Examples: >>> prec_service(id="228541") >>> prec_service(id="228541", sections="summary") # PlayMCP-safe

$0.05 USDC: predict configuration throughput, memory, and power from bounded StackBench evidence with confidence, missing metrics, and caveats.

Generate a .env-mcp configuration file for MCP server installation. Note: This tool works best with local CLI.

Find products with the highest agent readiness scores — products that are easiest for AI agents to integrate with. Sorted by compositeScore desc; supports skip/limit pagination. All readiness scores are 0-100, higher better. Calibration: <30 = not agent-ready (default minimumScore filter), 30-49 = early/limited, 50-69 = decent, 70-89 = strong, 90+ = exceptional. Ranking basis: compositeScore desc. Tier is NOT a tiebreaker here — buyer intent is technical fit, not paid placement. Every result carries { position (1-based, within the returned page), rank (0..1; 1.0 = top of this page) } so callers can merge results across tools consistently. Response: { products: [{ position, rank, slug, name, tagline, websiteUrl, tier (free|verified|featured), unverified (true when no approved vendor claim), verifiedAt (ISO; nullable), agentReadiness: { compositeScore, apiScore, protocolScore, sdkScore, integrationScore, dxScore } (each 0-100), mcp?: { hasMcpSupport, totalToolCount, serverCount } }] }.

Find B2B SaaS products that support a specific capability — an integration with a named service ('salesforce-integration'), a data format ('xrechnung-support'), an industry standard ('eclass-support'), or a compliance certification ('soc2'). Accepts either a canonical capability slug or natural language; resolves to a structured capability when possible. Ranking basis: currentScore desc (computed editorial score), then name. Paid tier is NOT a ranking input — it appears only as an annotation. Every result carries { position (1-based), rank (0..1; 1.0 = top, scales linearly down by ordinal position) } so callers can merge results across tools consistently. Response: { capability, matchType (none|exactSlug|canonicalSlug|nlpFallback — exactSlug & canonicalSlug are deterministic; nlpFallback is heuristic), resolvedFeatures[], products[] }. Each product: { position, rank, slug, name, tagline, websiteUrl, tier, unverified (true when no approved vendor claim), verifiedAt, evidence[] (per-claim: featureSlug, evidenceUrl, notes, source, confidence) }. Empty: { capability, matchType, message, suggestedSlugs[] } when no capability matched, or products: [] when capability matched but no products claim it yet.

Get full details for a product by slug, including MCP integration data, product-bound agent artifacts (Agent Skills, Grok Bots), and agent readiness scores. Agent artifacts are a property of the product — not directory categories. Response: { product: { slug, name, tagline, description, websiteUrl, logoUrl, pricingModel, currentScore (0-100), tier (free|verified|featured), unverified (true when no approved vendor claim), verifiedAt (ISO; absent if never crawled), categories[], knownLimitations?[] (sourced weaknesses, each with evidenceUrl — weigh before recommending), alternatives?[] (neutral, score-ranked same-category options, self excluded, houseProduct disclosed) }, mcp?: { hasMcpSupport, totalToolCount, totalUseCount, servers[] }, agentArtifacts[] (kind agentSkill|grokBot, install URLs, related product slugs), agentReadiness?: { compositeScore (0-100), aiSummary } }. Errors: { error: { code: 'not_found', ... } }.

Get MCP server setup instructions for a product. Returns available servers, their tools, connection details, and whether they support remote (hosted) access. Each server carries a machine-usable connect block: { transport ('http'|'local'), url, mcpJson (paste-ready snippet), claudeMcpAddCommand (`claude mcp add ...`), installLinkUrl (a tracked link that routes through Revuo for vendor attribution, then redirects to the product) }. For remote servers use mcpJson/claudeMcpAddCommand directly; for local servers follow repositoryUrl. Each server also carries schema { hash, stable, lastChangeAt } — cache the hash and pass it to tools.changes(knownHash) later to detect tool-schema drift (rug-pull / tool-poisoning). Response when MCP support exists: { product: { slug, name, websiteUrl, tier, unverified, verifiedAt }, hasMcpSupport: true, totalToolCount, servers[], agentReadiness? }. Response when product exists but lacks MCP: { product: {...}, hasMcpSupport: false, message }. Errors: { error: { code: 'not_found', ... } }.

Search for B2B SaaS products by name OR by capability. The query is first resolved against the canonical capability taxonomy (e.g. 'salesforce-integration', 'xrechnung-support', 'soc2'); on hit, products that claim that capability are returned. Falls back to name/slug/tagline substring search. Optional category scope. Ranking basis: currentScore desc (computed editorial score), then name. Paid tier is NOT a ranking input — tier appears only as an annotation on results. Every result carries { position (1-based), rank (0..1; 1.0 = top, scales linearly down by ordinal position) } so callers can merge results across tools consistently. Response: { query, matchType (none|exactSlug|canonicalSlug|nlpFallback), resolvedCapabilities[], products[] }. Each product carries { position, rank, tier (free|verified|featured — annotation only), houseProduct (true = built by Revuo's founder; conflict-of-interest disclosure), sponsored (true = paid Featured placement), unverified (true when the listing has no approved vendor claim; omitted otherwise — absence means an approved vendor claim, NOT crawl freshness; use verifiedAt for that), verifiedAt (ISO timestamp of last claim crawl; absent if never crawled), currentScore (0-100), compositeScore (agent-readiness 0-100, nullable), matchedCapability (true if surfaced by capability path) }. Errors: { error: { code: 'not_found'|'bad_input', ... } }.

List a project's stored assets (product photos, logos) with their URLs, for use as reference images.

[write] Update a project's brand brief (product summary, target audience, value proposition, industry, keywords). Sharpening the brief improves every later generation.