{"data":{"slug":"juyterman1000-entroly","name":"entroly","tagline":"Know exactly what your AI agent saw.","github_url":"https://github.com/juyterman1000/entroly","owner":"juyterman1000","repo":"entroly","owner_avatar_url":"https://avatars.githubusercontent.com/u/208309368?v=4","primary_language":"Python","stars":433,"forks":70,"topics":["agent","agent-memory","ai-agents","ai-coding-agents","claude-code","codex","context-compression","context-engineering","context-optimization","context-window","developer-tools-ai-agent","github-copilot","graph","hallucination-detection","harness-engineering","llm","loop-engineering","mcp","openclaw","token-optimization"],"archived":false,"github_pushed_at":"2026-08-04T08:38:06+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/juyterman1000-entroly","markdown_url":"https://www.graphcanon.com/tools/juyterman1000-entroly.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/juyterman1000-entroly","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=juyterman1000-entroly","description":"AI context optimization platform for files, conversations, RAG, code, logs and AI agents with context compression, evidence preservation, content-addressed recovery and auditable Context Receipts.","homepage_url":"https://juyterman1000.github.io/entroly/docs/index.html","license":"Apache-2.0","open_issues":6,"watchers":6,"ai_summary":"Local context-control plane for AI coding agents that manages evidence selection, compresses and keeps caches hot, verifies answers, and serves as an MCP/proxy/SDK for Cursor, Claude Code, Codex, and Aider among others.","readme_excerpt":"## Install\n\n> **Not sure which one?** Pick **Python**. It's the complete version and what\n> most people use. The others are alternate ways to run the same engine.\n\n| Platform | Install | What you get |\n|---|---|---|\n| 🐍 **Python** (pip) — *recommended* | `pip install -U entroly` | Everything: the command-line tool, the server your AI editor talks to, and the code library |\n| 📦 **Node / npm** | `npm install -g entroly` | The same engine, if you'd rather not install Python |\n| 🦀 **Rust** (source build) | `cd entroly-core && cargo build --release --bin entroly-rs --features proxy` | One self-contained program, no Python or Node needed |\n| 🍺 **Homebrew** | `brew install juyterman1000/entroly/entroly` | The command-line tool on macOS/Linux |\n| 🐳 **Docker** | `docker pull ghcr.io/juyterman1000/entroly:latest` | Runs in a container, nothing installed on your machine |\n\n**Now check that it worked — free, offline, no API key:**\n\n```bash\ncd /your/repo\nentroly verify-claims   # checks the install really does what this page claims\nentroly simulate        # shows how much smaller YOUR project would get\n```\n\n<sub>Both run locally. Neither one calls an AI or costs anything.</sub>\n\nExtras (`entroly[proxy]`, `entroly[native]`, `entroly[full]`), the standalone\nRust binary, and uninstall steps: [Engine & install options](docs/DETAILS.md#engine--install-options).\n\n---","github_created_at":"2026-03-07T23:03:02+00:00","created_at":"2026-07-11T23:37:01.590294+00:00","updated_at":"2026-08-04T12:01:04.288358+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"}],"tags":[{"slug":"ai-agents","name":"ai-agents"},{"slug":"context-compression","name":"context-compression"},{"slug":"hallucination-detection","name":"hallucination-detection"},{"slug":"token-optimization","name":"token-optimization"}],"trust":{"provenance":{"is_fork":false,"github_id":1175591394,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-04T12:01:03.338Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":30,"days_since_push":0,"last_release_at":"2026-08-04T08:12:49Z"},"security_summary":{"status":"findings","scanner":"mcp_manifest@v1","low_count":0,"high_count":0,"last_scan_at":"2026-07-11T23:37:04.824Z","medium_count":1,"scan_profile":"mcp_manifest","critical_count":0}},"capability_facts":{"mcp":{"source":"repo_scan","observed_at":"2026-08-04T12:01:03.805Z","server_manifest":false},"scan":{"source":"repo_scan","observed_at":"2026-08-04T12:01:03.805Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-08-04T12:01:03.805Z","managed_saas":false},"has_cli":{"value":true,"source":"pyproject.toml:[project.scripts]","observed_at":"2026-08-04T12:01:03.805Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-04T12:01:03.805Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-08-04T12:01:03.805Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-04T12:01:03.805Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When you require proof of evidence selection to ensure transparency in model decisions, use Entroly.","Use Entroly when working on projects that demand context-control and auditing across multiple coding agents like Cursor or Claude Code."],"when_not_to_use":["Avoid using Entroly if your AI workflows are already finely optimized for minimal intervention and do not benefit from additional context management layers.","Do not use Entroly if you have no need for replayable Context Commits, which Entroly offers to trace evidence selection and omissions."],"source":"enrich:decision_facts","observed_at":"2026-07-17T06:19:01.985Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Know exactly what your AI agent saw with Entroly."}]}}