AFL++ MCP server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@AFL++ MCP servercreate a new workspace named myfuzz"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
AFL++ MCP server
Model Context Protocol (MCP) server for AFL++.
This repo includes an AFLplusplus checkout (git submodule update --init with --recursive if you need AFL++ optional mode submodules) and exposes an agent-friendly API for:
creating fuzzing workspaces,
instrumenting targets,
corpus import/minimization,
harness preflight (dry run / showmap),
starting/stopping AFL++ jobs,
polling structured status and triaging findings,
other stuff
Install
Build
npm install
npm run buildInstall in Codex CLI
Build first, then register the MCP server with Codex CLI:
codex mcp add aflpp --env AFLPP_MCP_ROOT="$PWD" -- node "$PWD/dist/index.js"Run via stdio
node dist/index.jsEnvironment variables
AFLPP_MCP_ROOT(default: current working directory)AFLPP_DIR(default:$AFLPP_MCP_ROOT/AFLplusplus) – must be insideAFLPP_MCP_ROOT
Other MCP client configs
Claude Desktop
Add to your mcpServers config (adjust paths):
{
"mcpServers": {
"aflpp": {
"command": "node",
"args": ["/home/kevinv/aflpp-mcp/dist/index.js"],
"env": {
"AFLPP_MCP_ROOT": "/home/kevinv/aflpp-mcp"
}
}
}
}Related MCP server: Azure AI Foundry MCP Server
How to use
MCP prompts
aflpp-agent-workflow: high-level end-to-end workflow (build -> corpus -> preflight -> fuzz -> triage).aflpp-harness-workplan: harness-first workflow (usage ->LLVMFuzzerTestOneInputharness -> genesis corpus -> CMPLOG/ASAN/vanilla builds -> launch commands).
MCP resources
aflpp://config: server configuration (workspace root, limits, allowlist).aflpp://docs/quickstart: some workflow notes.aflpp://docs/fuzzing_in_depth: AFL++'sfuzzing_in_depth.mdaflpp://docs/cmplog: AFL++'sinstrumentation/README.cmplog.mdaflpp://docs/env_variables: AFL++'sdocs/env_variables.mdaflpp://workspace/{name}/tree: high-level workspace treeaflpp://job/{job_name}/latest_status: latest parsed status snapshot for a jobaflpp://campaign/{campaign_name}/latest_status: latest parsed status snapshot for a campaign
MCP tools
aflpp.list_tools: List AFL++ MCP tools and their short descriptions.
aflpp.help: Get detailed help for a tool (schema + description).
aflpp.version: Get AFL++ and server version information.
aflpp.init_workspace: Create a workspace under
workspaces/<name>with standard subdirectories for inputs, outputs, targets, logs, repros, and reports.aflpp.detect_build_system: Detect a likely build system for a project path (heuristic).
aflpp.build_instrumented: Build a target with AFL++ compiler wrappers (and optional sanitizer profiles + build-time knobs) and store the artifact under the workspace
targets/directory.aflpp.build_cmplog_variant: Build a CMPLOG-instrumented variant (AFL_LLVM_CMPLOG=1) and store the artifact under the workspace
targets/directory.aflpp.import_corpus: Import a seed corpus from a file or directory into
workspaces/<ws>/in/<corpus_name>.aflpp.list_corpus: Summarize a corpus directory (file count and total size).
aflpp.list_builtin_dictionaries: List AFL++ builtin dictionaries shipped in
AFLplusplus/dictionaries.aflpp.attach_dictionary: Attach a dictionary file to a job name (stored as a job config to be used by
aflpp.start_fuzz).aflpp.dry_run: Run a short harness validation directly against the target (not
afl-fuzz) to check input mode, stability, timeouts, and basic performance.aflpp.showmap: Run
afl-showmapfor a single testcase and return a summary of the trace.aflpp.coverage_summary: Measure corpus coverage using
afl-showmap -Con an AFL++ output directory (best-effort parsing).aflpp.analyze_testcase: Run
afl-analyzeon a testcase to identify critical input regions.aflpp.preflight_checks: Run lightweight preflight checks before starting
afl-fuzz(core_pattern, CPU scaling, corpus non-empty).aflpp.start_fuzz: Start an
afl-fuzzjob in the workspace (non-blocking; supports common afl-fuzz knobs + allowlisted env overrides).aflpp.start_fuzz_cluster: Start a multi-instance
afl-fuzzcampaign (master + secondary instances; supports per-instance overrides).aflpp.stop_fuzz: Stop a running
afl-fuzzjob by PID (SIGTERM then SIGKILL).aflpp.status: Get job status by parsing
fuzzer_statsand queue/crashes/hangs counts (with deltas since last call).aflpp.campaign_summary: Summarize a multi-instance campaign by parsing
fuzzer_statsfor each instance directory.aflpp.whatsup: Run
afl-whatsupon an AFL++ output directory.aflpp.generate_progress_plot: Generate an AFL++ progress plot for a job or campaign (wraps
afl-plot).aflpp.list_findings: List crash and hang findings with stable IDs and paths.
aflpp.repro_crash: Reproduce a finding by running the target command directly with the testcase and write a repro bundle under
repros/.aflpp.crash_report: Write a crash report for a finding (dedup signature + repro info + sanitizer frames if present).
aflpp.casr_report: Generate clustered crash reports using
casr-afl(if installed).aflpp.minimize_corpus: Minimize a corpus using
afl-cminand store it as a new corpus directory in the workspace.aflpp.minimize_testcase: Minimize a single testcase using
afl-tminand store the minimized testcase underrepros/.aflpp.suggest_fuzz_cluster_mix: Suggest a multi-core campaign mix (
instance_overrides) foraflpp.start_fuzz_cluster.
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