Agent Infrastructure✦
Agentic Schema Translation Semantic Normalizer
Normalize and translate structured data schemas for reliable agent workflows.
View source and documentation →
GenPark MCP Directory
Build Agents That Do Useful Work
Open, practical capabilities for product research, creator intelligence, marketing analysis, and reliable agent workflows.
Connect to the GenPark MCP endpoint →38 public skillsOpen source on GitHub
Marketing Intelligence✦
Multivariate Ad Creative Fatigue Auditor
Detect creative fatigue patterns and produce evidence-based refresh signals.
View source and documentation →Agent Reliability✦
Autonomous Deadlock Race Condition Detector
Inspect distributed agent workflows for deadlocks, races, and coordination hazards.
View source and documentation →Observability✦
Agent Session Replay Behavioral Audit Recorder
Record agent actions and create structured behavioral audit evidence.
View source and documentation →Safety✦
Prompt Injection Jailbreak Firewall Sentinel
Identify suspicious instruction patterns and return actionable safety findings.
View source and documentation →Context Engineering✦
Dynamic Context Pruning Needle Retriever
Select high-value context under token, relevance, and latency constraints.
View source and documentation →Creator Intelligence✦
Influencer Creator Fit Scoring
Score creator fit against campaign requirements, audience evidence, and constraints.
View source and documentation →Product Research✦
Evidence Backed Product Comparison
Compare products with structured criteria, tradeoffs, source notes, and confidence signals.
View source and documentation →Research Intelligence✦
Realtime Search Citation Grounder
Organize retrieved evidence into traceable claims, citations, and confidence signals.
View source and documentation →Developer Tools✦
OpenAPI Contract Validator
Validate API contracts, detect schema mismatches, and produce actionable diagnostics.
View source and documentation →Observability✦
Agent Trace Cost Anomaly Detector
Analyze agent trace latency and token cost patterns to surface operational anomalies.
View source and documentation →Agent Infrastructure✦
Multimodal Query Planner
Turn mixed text and image requests into explicit, testable execution plans.
View source and documentation →Agent Reliability✦
Workflow Failure Replay Diagnostics
Replay failed workflow steps and return structured root-cause diagnostics.
View source and documentation →Safety✦
Agent Policy Risk Gate
Evaluate proposed agent actions against explicit policy rules before execution.
View source and documentation →Data Engineering✦
Structured Synthetic Data Evolution Generator
Generate structured synthetic records with controlled complexity and validation checks.
View source and documentation →Search Infrastructure✦
Hierarchical Vector Index Searcher
Build and query hierarchical vector indexes for fast approximate similarity retrieval.
View source and documentation →Agent Orchestration✦
Multi Agent Debate Consensus Protocol
Coordinate structured agent perspectives and produce auditable consensus outcomes.
View source and documentation →Growth Analytics✦
Cohort Retention Churn Calculator
Calculate cohort retention, churn patterns, and hazard signals from event records.
View source and documentation →Market Research✦
Competitive Market Intelligence Synthesizer
Combine structured market signals into transparent competitive intelligence briefs.
View source and documentation →Security✦
Automated Secret Detection Security Gatekeeper
Scan source content for exposed secrets and return actionable security gate results.
View source and documentation →Commerce Intelligence✦
Conversational Commerce Recommendation Engine
Turn shopper intent, constraints, and preferences into explainable product recommendations.
View source and documentation →Cart Optimization✦
Agentic Cart Bundle Affinity Recommender
Identify complementary products and explain bundle recommendations for a shopping cart.
View source and documentation →Checkout Automation✦
Agentic Checkout Orchestrator
Coordinate checkout steps, confirmation gates, and safe handoffs for commerce agents.
View source and documentation →Catalog Intelligence✦
Commerce Catalog Optimization
Prepare product catalog attributes and content for reliable agent discovery and ranking.
View source and documentation →Pricing Intelligence✦
Competitor Price Monitor
Compare market price signals and return transparent monitoring and alert recommendations.
View source and documentation →Order Operations✦
Autonomous Post Purchase RMA Tracker
Track post-purchase return workflows, status changes, and customer resolution steps.
View source and documentation →Conversion Optimization✦
Coupon Recommendation Engine
Evaluate eligible discounts and return the strongest applicable offer under clear rules.
View source and documentation →Product Data✦
Cross Merchant SKU Validator
Validate SKU specifications, compatibility attributes, and normalized product identities.
View source and documentation →Lifecycle Commerce✦
Abandoned Cart Recovery
Create personalized recovery sequences for incomplete shopping journeys.
View source and documentation →Creator Commerce✦
Creator Affiliate Commerce Storefront
Organize creator-led product collections, recommendations, and attribution-ready storefronts.
View source and documentation →Commerce Operations✦
Supply Chain Demand Inventory Optimizer
Forecast demand and surface inventory actions that reduce stockout and overstock risk.
View source and documentation →Agent Commerce✦
Agent To Agent Commerce Representative
Represent product and brand commerce context in structured agent-to-agent workflows.
View source and documentation →Commerce Infrastructure✦
Agent Commerce Protocol
Define a practical protocol layer for agent-led product discovery, checkout, and merchant workflows.
View source and documentation →Commerce Infrastructure✦
Agent Commerce Skill
Equip AI agents with structured commerce context for product research, recommendations, and buying workflows.
View source and documentation →Agent Infrastructure✦
MCP Protocol Bridge
Bridge MCP-compatible agents to reusable tools and services with predictable input and output contracts.
View source and documentation →Product Infrastructure✦
Agent-Ready Catalog
Prepare product catalogs for reliable agent discovery with normalized fields, constraints, and buying context.
View source and documentation →Performance✦
Semantic Cache Manager
Reuse semantically equivalent agent results to reduce latency, cost, and repeated workflow work.
View source and documentation →Observability✦
Agent Observability Monitor
Track agent workflow health, latency, failures, and operational signals in a structured monitoring layer.
View source and documentation →GenPark MCP questions
What can GenPark MCP skills do?
GenPark MCP skills give compatible AI agents reusable capabilities for product research, commerce intelligence, creator analysis, marketing workflows, and agent reliability. Each skill describes a focused input and output contract so an agent can select a tool for a specific task.
What is MCP used for in an AI workflow?
MCP is a standard way for an AI application to discover and call external tools and data sources. In a GenPark workflow, MCP can connect an agent to structured research, comparison, catalog, monitoring, or automation capabilities without hard-coding every integration into the model.
How does GenPark support reliable agent work?
GenPark skills make agent work more reliable by separating a task into explicit capabilities, inputs, outputs, evidence, and safety checks. Skills such as citation grounding, policy risk gates, workflow replay, and observability help teams inspect results instead of treating every model response as an unexplained decision.
Which GenPark MCP skill should I start with?
Start with the skill that matches the job: Evidence Backed Product Comparison for shopping research, Realtime Search Citation Grounder for sourced answers, Agent-Ready Catalog for product data, or MCP Protocol Bridge when you need to connect an MCP-compatible agent to reusable tools.