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Local context OS for AI coding agents: token optimization, MCP tools, receipts, exact recovery, verification, and SDK helpers.

Project description

Entroly

Know exactly what your AI agent saw.

Entroly is a local context control plane for AI coding agents. It selects the highest-value evidence under a token budget, records what was selected and omitted, keeps compressed context recoverable, and produces verifiable Context Commits and receipts.

Install

pip install -U entroly

Run the local, no-key verification path:

entroly verify-claims
entroly simulate

MCP server

Start the stdio MCP server directly:

entroly serve

Or use a package runner:

uvx --from entroly entroly serve
npx -y entroly-mcp serve

Entroly works with GitHub Copilot in VS Code, Claude Code, Cursor, Windsurf, Cline, Continue, Zed, and other MCP-compatible clients.

GitHub Copilot / VS Code

Create .vscode/mcp.json:

{
  "servers": {
    "entroly": {
      "type": "stdio",
      "command": "uvx",
      "args": ["--from", "entroly", "entroly", "serve"]
    }
  }
}

Or install through the MCP gallery after the official registry listing becomes available by searching for Entroly.

Claude Code

claude mcp add entroly -- uvx --from entroly entroly serve

Generic MCP configuration

{
  "mcpServers": {
    "entroly": {
      "command": "uvx",
      "args": ["--from", "entroly", "entroly", "serve"]
    }
  }
}

What Entroly adds

  • Context selection under explicit token and cost budgets
  • Context Commits linking selected, omitted, and recoverable evidence
  • Context Receipts for replay, audit, and omission explanations
  • Exact recovery of compressed fragments through stable handles
  • Local verification through WITNESS and receipt checks
  • Context Check coverage evidence for changed files and CI risk gates
  • Rust and WASM engines with a pure-Python fallback
  • Local-first operation with no outbound analytics by default

Links

MCP Registry identity

mcp-name: io.github.juyterman1000/entroly

Apache-2.0 licensed.

Project details


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