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Weavable

Give every AI agent persistent work context

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Weavable gives AI agents persistent, live work context from the tools your business already runs on. Through a single MCP endpoint, it turns scattered updates, relationships, and system changes into a usable context layer so agents can reason more accurately without constantly re-ingesting data. The result is lower token usage, better outputs, and more reliable agent behavior across real business workflows.

PH · launched May 11, 2026 · 234 upvotes (top 55%) · 2 views

Niche: ai agent memory infrastructure · 350 launches, 11 in the last 7 days ▼ -58% · Explore this niche →

Category and tags

  • Horizontal
  • Data infrastructure
  • B2B
  • AI-native
  • Commercial product
  • SaaS
  • Artificial Intelligence
  • Operations

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Could you build this?

Partial Creating a Model Context Protocol (MCP) server is simple, but building a real-time event ingestion and dynamic knowledge-graph reconciliation engine across disparate enterprise SaaS tools is technically demanding.

What it would actually take: A real version relies on a streaming event-driven architecture (e.g., Kafka, Flink) that connects to dozens of third-party SaaS APIs (Slack, Jira, GitHub, Notion) via webhooks and continuous polling. The hard part is constructing an incremental, real-time entity-relationship graph or memory store that tracks live state transitions and deduplicates context without exceeding agent token budgets. It requires data engineering expertise in knowledge graph construction, graph databases (Neo4j, Memgraph), and distributed sync protocols.

Competitors

Other products that read as similar to this one : 1071 launches clear the similarity bar, closest 8 shown.

Attention rank: #756 of 1072 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 192 days after the earliest competitor.

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