Reversecore MCP
Security-first Model Context Protocol server for reverse engineering, malware analysis, digital forensics, vulnerability research, and SAST.
Reversecore MCP gives MCP-compatible AI agents structured access to Radare2, r2ghidra, YARA, LIEF, Capstone, angr, Qiling harness generation, Volatility3, Scapy, and additional analysis engines. It is designed around explicit workspace boundaries, input validation, non-root containers, and security regression testing.
Installation
Full container image — recommended
The container image includes the supported native toolchain and is the most reproducible installation method:
docker run -i --rm \
-v /absolute/path/to/samples:/app/workspace \
-e REVERSECORE_WORKSPACE=/app/workspace \
-e MCP_TRANSPORT=stdio \
ghcr.io/sjkim1127/reversecore_mcp:3.0.4
Python package
Install the MCP server and all supported Python feature extras from PyPI:
pip install "reversecore-mcp[full]"
Native programs such as Radare2, YARA, Graphviz, Binwalk, and The Sleuth Kit must be installed separately when using the Python package directly.
Qiling isolation: the server can generate Qiling/AFL harnesses, but Qiling is intentionally not installed by the
fullextra. Qiling 1.4.6 depends on a legacy Pillow line with known vulnerabilities. Execute generated harnesses only in a separate disposable sandbox; seedocs/EMULATION.mdin the repository.
Run the stdio server with:
MCP_TRANSPORT=stdio \
REVERSECORE_WORKSPACE=/absolute/path/to/samples \
reversecore-mcp
MCP client configuration
{
"mcpServers": {
"reversecore": {
"command": "reversecore-mcp",
"env": {
"MCP_TRANSPORT": "stdio",
"REVERSECORE_WORKSPACE": "/absolute/path/to/samples"
}
}
}
}
Capabilities
- Static analysis, disassembly, decompilation, cross-references, and CFG recovery
- Malware triage, IOC extraction, YARA scanning, and MITRE ATT&CK mapping
- Symbolic execution, emulation harness generation, fuzzing, and ROP analysis
- Memory, disk, network, and host-artifact forensics
- Python and C/C++ source-code security analysis
- Structured evidence, session tracking, metrics, and report generation
Security model
Reversecore MCP processes potentially hostile binaries. Use a dedicated workspace and prefer the hardened container configuration for untrusted samples. The project CI includes dependency auditing, CodeQL, secret scanning, container scanning, path-boundary tests, fuzzing, and network-isolation checks.
Detailed configuration, tool documentation, Docker Compose profiles, and client examples are available in the GitHub repository.
Registry identity
- MCP Registry name:
io.github.sjkim1127/reversecore-mcp - PyPI package:
reversecore-mcp - OCI image:
ghcr.io/sjkim1127/reversecore_mcp
License
MIT
Metadata
Release files for reversecore-mcp 3.0.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| reversecore_mcp-3.0.4.tar.gz | 479.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| reversecore_mcp-3.0.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.0 MB
Release files / reversecore_mcp-3.0.4.tar.gz
| Download URL | reversecore_mcp-3.0.4.tar.gz |
|---|---|
| Size | 479.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
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PyPI Publish Attestation
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Signed by GitHub Actions, verified by PyPI on Sep 18, 2026.
Transparency logRelease files / reversecore_mcp-3.0.4-py3-none-any.whl
| Download URL | reversecore_mcp-3.0.4-py3-none-any.whl |
|---|---|
| Size | 531.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
e63f176f9d7a6f77d870fbd3f2de4959095003446b21e5a15a112aa0c3783a05
|
|
BLAKE2b-256 checksum How to use checksums |
9bc270535b94875e078211a6cbf76ca54bb2e83fbd10861d8e4f52862f8188c0
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 18, 2026.
Transparency log