Why this fit
Teams evaluating AI models, assistants and generative workflows, particularly AI agents that connect over MCP and privacy-sensitive setups — free to start, source available on GitHub.
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AI / Catalogue record

Catalogue record
github.com
🐍 🦀 🏠 🍎 🪟 🐧 - Auditable context control plane and MCP server for AI coding agents. Compresses context 70–95% (BM25 + entropy + dep-graph kna...
Field notes
🐍 🦀 🏠 🍎 🪟 🐧 - Auditable context control plane and MCP server for AI coding agents. Compresses context 70–95% (BM25 + entropy + dep-graph knapsack), stabilizes prompt prefixes for provider cache discounts, routes easy tasks to cheaper models (RAVS Bayesian router), and verifies answers locally with WITNESS hallucination guard (0.844 AUROC, $0, 3 ms). MemoryOS adds local budget-aware working/episodic/semantic memory with decay, safety scanning, and durable persistence. 38 agent integrations (C...
Best for
Teams evaluating AI models, assistants and generative workflows, particularly AI agents that connect over MCP and privacy-sensitive setups — free to start, source available on GitHub.
Known limitations
Teams that need a vendor SLA before adopting a free tool — check the project's support terms first.
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Evidence summary
Why this fit
Teams evaluating AI models, assistants and generative workflows, particularly AI agents that connect over MCP and privacy-sensitive setups — free to start, source available on GitHub.
Known limitations
Teams that need a vendor SLA before adopting a free tool — check the project's support terms first.
Catalogue confidence
Catalogue data checked Oct 27, 2026.
GitHub-backed record with source-attributed context.
Repository context
GitHub / juyterman1000/entroly
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