rea-python(rea-mcp)

Reverse engineer anything from your terminal or agent — one CLI and one MCP server.

Attribution and disclaimer

This is an unofficial Python port of morluto/rea. The original project is a TypeScript implementation. This port exists because our Python-based AI agent products (aacode, fastclaw) need a native Python integration. Not affiliated with or endorsed by the original authors. Licensed under MIT.

See DISCLAIMER.md for responsible-use guidance and THIRD_PARTY_NOTICES.md for dependency and tool notices.

Lawful use

The project's position on illegal or unauthorized use covers all REA versions, distribution channels, and platforms; each copy retains its applicable licenses.

REA is for lawful research, education, interoperability, software preservation, and analysis of software you own or are authorized to examine.

Commercial tools

You must legally obtain and be authorized to use commercial tools, including IDA Pro / Hex-Rays decompilers, Hopper, and JEB, under their applicable licenses. REA grants no tool license, key, or activation entitlement. Trials and demos remain subject to vendor terms, including user, feature, automation, and output sharing restrictions. Cracked copies, stolen keys, unauthorized key sharing, and bypassing license restrictions are not authorized. This guidance does not amend MIT or third-party licenses.

Deep-engine configuration

rea-python is a provider-neutral reverse-engineering engine that returns traceable, evidence-carrying, reusable results, exposed through a shared CLI and MCP (Model Context Protocol) server. Its design follows the ideas behind morluto/rea, including the Evidence model: every result carries its identity, confidence, authority, limitations, and unresolved unknowns, so an AI agent (or a person) can reason honestly instead of trusting a bare answer.

Status: alpha (0.1.5) — full original CLI/MCP surface (169 tool names, 153 CLI commands) with built-in static providers, the Evidence model, snapshot caching, deep-engine adapters, workflow/evidence tools, and gated runtime observation.

What you can analyze

External-tool providers are caller-supplied: rea-mcp never installs them and reports an actionable reason when one is missing (rea-mcp doctor). Cross-cutting tools: compare / compare-network-captures / compare-web-captures / compare-managed-members (target and Evidence diffs), build-reconstruction-obligation-ledger / evaluate-reconstruction-coverage (reconstruction), capture-process (bounded runtime capture), doctor (readiness), setup (client registration, plus --write-all and --install-skill), update, and evidence-export / evidence-import / inspect-analysis-view (portable Evidence).

All analysis runs locally. rea-mcp never uploads your target.

Client schema profiles

Tool schemas can be projected per client to fit hosts with small frame or schema limits. Set REA_MCP_CLIENT to a preset (generic, claude, cursor, opencode, vscode/code, zed, minimal), or override with REA_MCP_INPUT_SCHEMA_PROFILE (full/compact) and REA_MCP_OUTPUT_SCHEMA_PROFILE (full/off). rea-mcp schema-matrix prints the full matrix; REA_MCP_COMPACT_BUDGET_BYTES caps a single compacted schema.

Quick start

pip install rea-mcp             # PyPI distribution name is "rea-mcp"
rea-mcp --help                  # "rea" and "rea-python" are installed as alias commands too
rea-mcp inspect-binary-layout /path/to/program --json

As an MCP server (stdio) — rea-mcp, rea, and rea-python are interchangeable, as are python -m rea_mcp, python -m rea, and python -m rea_python:

rea-mcp mcp     # or: rea mcp   |   rea-python mcp
rea mcp

Output is JSON by default; a bare --json flag is accepted (before or after the command) for compatibility.

Import names

The implementation package is rea_mcp. Compatibility aliases make import rea and import rea_python resolve to the same module objects, so all three import paths are interchangeable:

import rea_mcp  # implementation
import rea  # alias, same objects
import rea_python  # alias, same objects

Design principles

1. Dependencies flow inward: domain → contracts → providers → application → cli/mcp.
2. Evidence first: observations, derivations, inferences, and unknowns are distinguished.
3. Ownership and cleanup: resources are only cleaned by their owner; failures stay explicit.
4. Token-first performance: summaries, paging, and retained evidence keep agent context small.

Development

python -m venv .venv && . .venv/bin/activate
pip install -e ".[dev]"
pytest
ruff check .
mypy

License

MIT. rea-mcp is an independent, unofficial Python port; it is not affiliated with or endorsed by the authors of REA. See LICENSE and DISCLAIMER.md.