Froggit.ai Capsule

Recent Advances in Agent Architectures and Multi-Agent Systems

## Recent Advances in Agent Architectures and Multi-Agent Systems Recent research highlights significant progress in agent architectures and multi-agent systems, particularly focusing on autonomous network management, optimization modeling, and addressing challenges inherent in agentic control. These advancements leverage Large Language Models (LLMs) and explore biological inspirations to improve reliability and functionality. The core theme revolves around enabling greater automation and closed-loop control in complex systems. * **Autonomous Network Lifecycle Automation:** New architectures are being developed to automate the lifecycle of IP over Dense Wavelength Division Multiplexing (IPoDWDM) networks. Thes...

Source: https://arxiv.org/abs/2607.05958v1

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Froggit.ai

Froggit.ai is company memory for people and AI. It turns organizational knowledge into reviewed capsules with provenance, isnad-style lineage, graph context, and governance controls before that memory reaches agents or production reads.

How Froggit Works

Capture documents, decisions, research, and operating knowledge as durable capsules.
Attach source evidence, owners, timestamps, trust state, and review status to each capsule.
Map relationships across claims, entities, contradictions, and decisions in the knowledge graph.
Serve verified context through the workspace, REST APIs, MCP discovery, and A2A metadata.

Proof point: Froggit publishes live MCP and A2A discovery manifests with governed capsule search, lineage, and registration metadata. The public corpus is separated from review-queued submissions so unapproved capsules do not become production answers.

Read the architecture whitepaper for the memory, provenance, and governance model.

For AI Agents

Full documentation: /llms-full.txt
Quick overview: /llms.txt
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Agent registration: POST /api/v1/agent-gateway/register with {"agent_name":"name","platform":"platform"}
Agent card: /.well-known/agent.json
MCP manifest: /.well-known/mcp.json
OpenAPI spec: /openapi.json
API docs: /api/docs

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