Borrowing it
Nothing to install: this file belongs to karimodm/angrMCP. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/karimodm/angrMCP/main/AGENTS.mdgit clone --depth 1 https://github.com/karimodm/angrMCPWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/karimodm/angrmcp/agents-md)<a href="https://agentmods.dev/instructions/karimodm/angrmcp/agents-md"><img src="https://agentmods.dev/badge/instructions/karimodm/angrmcp/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/karimodm/angrmcp/agents-md"><img src="https://agentmods.dev/badge/instructions/karimodm/angrmcp/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.01569 | $0.01569 |
| Opus 5.5 | $0.00628 | $0.00628 |
| Sonnet 5.5 | $0.00314 | $0.00314 |
| Haiku 4.5 | $0.00157 | $0.00157 |
Grade A, and why
angrMCP AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Operations Guide
This document records the workflow followed so far, key decisions, and rules for future human or agent contributors working on the angr MCP server project.
Environment & Tooling
- Python: 3.13 (system interpreter). A dedicated virtual environment is
created via
uv venv .venv. KeepUV_CACHE_DIR=.uv-cacheto store build artifacts locally. - Dependencies: install
claripyandangrfrom PyPI inside the virtual environment (uv pip install --python .venv/bin/python claripy angr). - Testing: run
.venv/bin/python -m unittest discover teststo cover both the synthetic sample binary suite and the angr CTF Phase 1 regressions. - Binary samples: Phase 1 tests rely on bundled 32-bit angr CTF binaries.
Native replay assertions will skip automatically if
/lib/ld-linux.so.2(or equivalent) is unavailable. The legacy sample binary still compiles on the fly and therefore continues to require a working C compiler (ccorgcc).
Repository Layout Snapshot
angr_mcp/– MCP server implementation and runtime registry.resources/– Bundled reference material and companion codebases:resources/angr– Upstream angr source tree (currently unused for installs; PyPI packages are consumed instead).resources/awesome-angr– Community exploration techniques dynamically imported by the server when requested.resources/angr_ctf– Capture-the-flag training levels and build scripts for learning angr-based symbolic exploitation (MetaCTF workshop content).resources/dAngr– dAngr examples and docs for additional exploration strategies.resources/GhidraMCP– Shared assets for coordinating workflows with the Ghidra MCP server.
angr_mcp/utils/– Shared binary-inspection and state-mutation helpers used by handlers and tests.tests/test_mcp_server.py– Integration tests; doubles as executable examples for the handler workflow.tests/test_phase1_ctf.py– Automates angr CTF levels 00–04 through MCP handlers, asserting predicate metadata, register/stack tooling, and native replay.tests/test_deep_call_partition.py– Builds a deeply nested binary and exercises call-chain recovery, state-budget limits, and chunked symbolic execution to reach a buried function.pyproject.toml– Minimal configuration foruvenvironment management.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 131 lines · 1,569 tokens per session scan A 2fe915dd74de
angrMCP AGENTS.md is an instructions file published in the GitHub repository karimodm/angrMCP (10 stars, last pushed 10mo ago), licensed MIT. It adds 1,569 tokens to every session, about $0.0063 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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