xagi-lab/melra
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Open-source local MCP execution runtime for agents: policy-gated tool calls, scoped approvals, verified outcomes, durable receipts, and recovery after interruptions.
Обзор
**odular **xecution **ayer for **eliable **utonomy An open-source : the layer every agent action passes through on its way to your files, terminal, browser, desktop and APIs. It checks each action against policy, requests approval when needed, verifies declared evidence, and keeps a redacted receipt. For each task, MELRA dispatches mutations at most once; uncertain outcomes are parked for reconciliation instead of replay. Exactly-once external effects still depend on the provider. The local runtime is tested end to end, but APIs may change before 1.0. Use an isolated workspace, keep domain and command allowlists narrow, and read every approval before you give it. AI agents no longer just talk. They edit files, run commands, click through websites and call APIs on your behalf. Four questions come with that, and most agents answer them differently, or not at all: Every action is checked against policy, and checked again at the moment it runs.
README
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MELRA
Modular Execution Layer for Reliable Autonomy
Your AI agent decides what to do. MELRA governs how tool calls are authorized, verified, and recovered.
An open-source local execution runtime for agent tool calls you route through MELRA. It checks each call against policy, requests approval when needed, verifies declared evidence, and keeps a redacted receipt of what runs to an outcome. For each task, MELRA dispatches mutations at most once; uncertain outcomes are parked for reconciliation instead of replay. Exactly-once external effects still depend on the provider. Calls made through other tools remain outside MELRA’s control.
Установка
npx @melra/cli@alpha setup