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  • A
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    quality
    A
    maintenance
    A passive context server that stores product knowledge, generates structured prompts, and coordinates multi-agent workflows via the Model Context Protocol, enabling AI coding tools to share a full picture of the product.
    Elastic 2.0
  • A
    license
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    quality
    B
    maintenance
    Enables AI agents to capture, store, and retrieve durable learnings from projects via MCP tools, providing a queryable memory of product and technical lessons across repos.
    MIT
  • A
    license
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    quality
    B
    maintenance
    Enables coding agents to access structured product context (decisions, goals, evidence) from meetings and tools, ensuring they build from actual product decisions.
    4
    1
    MIT
  • A
    license
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    quality
    D
    maintenance
    Enables AI coding agents to access persistent, structured product context (personas, journeys, specs, decisions, domain rules) on demand, eliminating the need to re-explain product knowledge each session.
    25
    1
    MIT
  • A
    license
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    quality
    D
    maintenance
    Provides structured access to actionable insights, frameworks, and leadership advice curated from episodes of Lenny's Podcast. It enables users to search for specific product management situations, compare guest perspectives, and browse a catalog of industry frameworks.
    MIT
  • F
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    quality
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    maintenance
    Integrates the OpenViking context database with Cloudwise SA Workflow Skills to enable semantic search and access to product catalogs or solution templates. It supports hierarchical context loading for optimized token usage and includes a mock mode for testing without a live backend.
  • F
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    quality
    D
    maintenance
    Provides hierarchical RAG over 299 Lenny Rachitsky podcast transcripts for product development brainstorming and insight retrieval. It enables semantic search across topics, insights, and examples to surface expert advice on product management and growth.
    5
  • A
    license
    A
    quality
    A
    maintenance
    8 standalone MCP servers for SMBs — Guardrails (prompt injection, PII, secrets detection), FinOps (AI cost tracking and budgets), Observability (agent tracing), Smart Router (17+ models, 9 providers), Trust Score (governance scoring 0-100), Memory (persistent agent memory), ThinkSecure (runtime security + SOC2/GDPR audit), and A2A Lite (agent-to-agent protocol). 37 tools total, TNC credits
    4
    1
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    An MCP server that reads a team's interviews, tickets, and docs to build a model of the product, exposing tools to ask questions, list contradictions and gaps, and draft documents, with all answers citing their source fragments.
    6
    10
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    A read-only MCP server providing tools to search and retrieve insurance product information, coverage details, and compare policies from a pre-built knowledge graph of Belgian insurance products, with verbatim citations from source PDFs.
    10
    MIT
  • A
    license
    A
    quality
    B
    maintenance
    French marketplace MCP server for artisanal hemp/CBD products. Exposes 10 tools (product search, personalized recommendations, comparison, producer info with geolocation, stock availability, market prices "Bloomberg CBD", complete CBD guides, news, wiki search, full wiki article) + 4 resources (catalog, producers map, CBD reference covering France + 12 EU countries, wiki catalog).
    10
    MIT
  • A
    license
    A
    quality
    B
    maintenance
    Generate production-ready Product Requirement Documents with full AINative platform awareness and persistent memory. Enables AI agents to create, validate, and manage PRDs using ZeroDB for cross-session storage and 18 tools including generation, templates, validation, and semantic search.
    23
    250
    MIT
  • A
    license
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    quality
    B
    maintenance
    Vibsync gives Claude Code, Cursor, Codex, and other AI coding agents long-term team memory and live work context. It carries both what the team knows — discoveries, fixes, failed approaches, product rules, and decisions — and what the team is doing now — questions, tasks, ownership, and active work areas — across sessions and machines.
    MIT