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Meldwork
by Ryder-MHumble
Local-first workspace for evidence-aware multi-agent orchestration
JavaScript
Updated Sep 4, 2026
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Overview
Provides a local-first workspace for building, running, and coordinating multiple AI agents with scoped permissions and human-in-the-loop control. Uses an evidence-aware runtime that captures interaction logs and provenance so orchestration decisions can be reviewed and audited. Includes a CLI and Electron UI for interactive orchestration, scoped agent permissions, and reproducible runs. guardrails pattern Consensus-Based Decision Pattern
The Value Proposition
As agents collaborate and delegate, trust and traceability become primary concerns — not just raw performance. Meldwork surfaces the evidence, permissions, and human checkpoints needed to judge agent behavior and build an agent track record over time. That visibility makes it easier to evaluate agent reliability and diagnose multi-agent system failures before production. Chain of Thought Pattern
Best For
Developers and researchers building and testing multi-agent workflows who need local control, provenance, and human-in-the-loop governance. Model Context Protocol (MCP)
Use Cases
- Run reproducible multi-agent experiments with human checkpoints and recorded evidence
- Prototype agent delegation patterns and inspect agent decision provenance
- Manage scoped permissions and local governance for agents before production rollout
Works With
electronjavascriptnodejslocal-ai
Topics
acpagent-client-protocolagent-collaborationagent-coordinationagent-orchestrationagent-runtimeagent-workforceagentic-workflowai-agentai-agent-workspace+10 more
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Keywords
multi-agent trustevidence-awareagent orchestrationlocal-ai