codebase-memory-mcp

The fastest and most efficient code intelligence engine for AI coding agents. Full-indexes an average repository in milliseconds, the Linux kernel (28M LOC, 75K files) in 3 minutes. Answers structural queries in under 1ms. Ships as a single static binary for macOS, Linux, and Windows — download, run install, done.

High-quality parsing through tree-sitter AST analysis across all 158 languages, enhanced with Hybrid LSP semantic type resolution for Python, TypeScript / JavaScript / JSX / TSX, PHP, C#, Go, C, C++, Java, Kotlin, and Rust — producing a persistent knowledge graph of functions, classes, call chains, HTTP routes, and cross-service links. 14 MCP tools. Zero dependencies. Plug and play across 11 coding agents.

Research — The design and benchmarks behind this project are described in the preprint Codebase-Memory: Tree-Sitter-Based Knowledge Graphs for LLM Code Exploration via MCP (arXiv:2603.27277). Evaluated across 31 real-world repositories: 83% answer quality, 10× fewer tokens, 2.1× fewer tool calls vs. file-by-file exploration.

Security & Trust — This tool reads your codebase and writes to your agent configuration files. That is what it is designed to do. If you prefer to audit before running, the full source is here — every release binary is signed, checksummed, and scanned by 70+ antivirus engines. All processing happens 100% locally; your code never leaves your machine. Found a security issue? We want to know — see SECURITY.md. Security is Priority #1 for us.

Why codebase-memory-mcp

• Extreme indexing speed — Linux kernel (28M LOC, 75K files) in 3 minutes. RAM-first pipeline: LZ4 compression, in-memory SQLite, fused Aho-Corasick pattern matching. Memory released after indexing.
• Plug and play — single static binary for macOS (arm64/amd64), Linux (arm64/amd64), and Windows (amd64). No Docker, no runtime dependencies, no API keys. Download → install → restart agent → done.
• 158 languages — vendored tree-sitter grammars compiled into the binary. Nothing to install, nothing that breaks.
• 120x fewer tokens — 5 structural queries: ~3,400 tokens vs ~412,000 via file-by-file search. One graph query replaces dozens of grep/read cycles.
• 11 agents, one command — install auto-detects Claude Code, Codex CLI, Gemini CLI, Zed, OpenCode, Antigravity, Aider, KiloCode, VS Code, OpenClaw, and Kiro — configures MCP entries, instruction files, and pre-tool hooks for each.
• Built-in graph visualization — 3D interactive UI at localhost:9749 (optional UI binary variant).
• Infrastructure-as-code indexing — Dockerfiles, Kubernetes manifests, and Kustomize overlays indexed as graph nodes with cross-references. Resource nodes for K8s kinds, Module nodes for Kustomize overlays with IMPORTS edges to referenced resources.
• 14 MCP tools — search, trace, architecture, impact analysis, Cypher queries, dead code detection, cross-service HTTP linking, ADR management, and more.

Quick Start

One-line install (macOS / Linux):

curl -fsSL https://raw.githubusercontent.com/DeusData/codebase-memory-mcp/main/install.sh | bash

With graph visualization UI:

curl -fsSL https://raw.githubusercontent.com/DeusData/codebase-memory-mcp/main/install.sh | bash -s -- --ui

Windows (PowerShell):

# 1. Download the installer
Invoke-WebRequest -Uri https://raw.githubusercontent.com/DeusData/codebase-memory-mcp/main/install.ps1 -OutFile install.ps1

# 2. (Optional but recommended) Inspect the script
notepad install.ps1

# 3. Unblock the downloaded file (removes Mark-of-the-Web restriction added by browsers/Invoke-WebRequest)
Unblock-File .\install.ps1

# 4. Run it
.\install.ps1

Note: If you see a script execution policy error, run Set-ExecutionPolicy -Scope Process Bypass first, or invoke with PowerShell -ExecutionPolicy Bypass -File .\install.ps1.

Options: --ui (graph visualization), --skip-config (binary only, no agent setup), --dir=<path> (custom location).

Restart your coding agent. Say "Index this project" — done.

1. Download the archive for your platform from the latest release:

   • codebase-memory-mcp-<os>-<arch>.tar.gz (macOS/Linux) or .zip (Windows) — standard
   • codebase-memory-mcp-ui-<os>-<arch>.tar.gz / .zip — with graph visualization

2. Extract and install (each archive includes install.sh or install.ps1):

   macOS / Linux:

   bash

   tar xzf codebase-memory-mcp-*.tar.gz
   ./install.sh
   

   Windows (PowerShell):

   powershell

   Expand-Archive codebase-memory-mcp-windows-amd64.zip -DestinationPath .
   Unblock-File .\install.ps1
   .\install.ps1
   

3. Restart your coding agent.

The install command automatically strips macOS quarantine attributes and ad-hoc signs the binary — no manual xattr/codesign needed.

The install command auto-detects all installed coding agents and configures MCP server entries, instruction files, skills, and pre-tool hooks for each.

Graph Visualization UI

If you downloaded the ui variant:

codebase-memory-mcp --ui=true --port=9749

Open http://localhost:9749 in your browser. The UI runs as a background thread alongside the MCP server — it's available whenever your agent is connected.

Auto-Index

Enable automatic indexing on MCP session start:

codebase-memory-mcp config set auto_index true

When enabled, new projects are indexed automatically on first connection. Previously-indexed projects are registered with the background watcher for ongoing git-based change detection. Configurable file limit: config set auto_index_limit 50000.

Watcher registration is controlled separately by auto_watch (default true). Set config set auto_watch false to keep a session from registering its project with the background watcher — useful when working across many projects and you want each session contained to explicit indexing.

Keeping Up to Date

codebase-memory-mcp update

The MCP server also checks for updates on startup and notifies on the first tool call if a newer release is available.

Uninstall

codebase-memory-mcp uninstall

Removes all agent configs, skills, hooks, and instructions. Does not remove the binary or SQLite databases.

Features

Graph & analysis

• Architecture overview: get_architecture returns languages, packages, entry points, routes, hotspots, boundaries, layers, and clusters in a single call
• Architecture Decision Records: manage_adr persists architectural decisions across sessions
• Louvain community detection: Discovers functional modules by clustering call edges
• Git diff impact mapping: detect_changes maps uncommitted changes to affected symbols with risk classification
• Call graph: Resolves function calls across files and packages (import-aware, type-inferred)
• Dead code detection: Finds functions with zero callers, excluding entry points
• Cypher-like queries: MATCH (f:Function)-[:CALLS]->(g) WHERE f.name = 'main' RETURN g.name

Search

• Semantic search (semantic_query): vector search across the entire graph, powered by bundled Nomic nomic-embed-code embeddings (40K tokens, 768d int8) compiled into the binary — no API key, no Ollama, no Docker. 11-signal combined scoring (TF-IDF, RRI, API/Type/Decorator signatures, AST profiles, data flow, Halstead-lite, MinHash, module proximity, graph diffusion).
• BM25 full-text search via SQLite FTS5 with cbm_camel_split tokenizer (camelCase / snake_case aware)
• Structural search (search_graph): regex name patterns, label filters, min/max degree, file scoping
• Code search (search_code): graph-augmented grep over indexed files only

Cross-service linking

• HTTP route ↔ call-site matching with confidence scoring
• gRPC, GraphQL, tRPC service detection with protobuf Route extraction
• Channel detection (EMITS / LISTENS_ON) for Socket.IO, EventEmitter, and generic pub-sub patterns across 8 languages with constant resolution

Cross-repo intelligence

• CROSS_* edges link nodes across multiple repos indexed under the same store
• Multi-galaxy 3D UI layout for cross-repo architecture visualization
• Cross-repo architecture summary combining services, routes, and dependencies across the indexed fleet

Edge types (selected)

• CALLS, IMPORTS, DEFINES, IMPLEMENTS, INHERITS
• HTTP_CALLS, ASYNC_CALLS (cross-service)
• EMITS, LISTENS_ON (channels)
• DATA_FLOWS with arg-to-param mapping + field access chains
• SIMILAR_TO (MinHash + LSH near-clone detection, Jaccard scored)
• SEMANTICALLY_RELATED (vocabulary-mismatch, same-language, score ≥ 0.80)

Indexing pipeline

• 158 vendored tree-sitter grammars compiled into the binary
• Generic package / module resolution — bare specifiers like @myorg/pkg, github.com/foo/bar, use my_crate::foo resolved via manifest scanning (package.json, go.mod, Cargo.toml, pyproject.toml, composer.json, pubspec.yaml, pom.xml, build.gradle, mix.exs, *.gemspec)
• Infrastructure-as-code indexing — Dockerfiles, Kubernetes manifests, Kustomize overlays as graph nodes
• Hybrid LSP semantic type resolution for Python, TypeScript / JavaScript / JSX / TSX, PHP, C#, Go, C, C++, Java, Kotlin, and Rust — a lightweight C implementation of language type-resolution algorithms, structurally inspired by and compatible with major language servers including tsserver / typescript-go, pyright, gopls, Roslyn, Eclipse JDT, and rust-analyzer (parameter binding, return-type inference, generic substitution, JSX component dispatch, JSDoc inference for plain JS files, namespace + trait + late-static-binding resolution for PHP, file-scoped namespaces + records + LINQ method syntax for C#, class-hierarchy + overload + lambda resolution for Java, extension-function + scope-function resolution for Kotlin, trait-method + UFCS resolution for Rust)
• RAM-first pipeline: LZ4 compression, in-memory SQLite, single dump at end. Memory released after.

Distribution & operation

• Single static binary, zero infrastructure: SQLite-backed, persists to ~/.cache/codebase-memory-mcp/
• Auto-sync: Background watcher detects file changes and re-indexes automatically
• Route nodes: REST endpoints are first-class graph entities
• CLI mode: codebase-memory-mcp cli search_graph '{"name_pattern": ".*Handler.*"}'
• Available on: npm, PyPI, Homebrew, Scoop, Winget, Chocolatey, AUR, go install

Team-Shared Graph Artifact

Commit a single compressed file to your repo and your teammates skip the reindex.

.codebase-memory/graph.db.zst is a zstd-compressed snapshot of the knowledge graph that lives next to your source. When you index, the artifact is written or refreshed; when a teammate clones the repo and runs codebase-memory-mcp for the first time, the artifact is decompressed and incremental indexing fills in their local diff.

• Format: SQLite database, indexes stripped, VACUUM INTO compacted, then zstd 1.5.7 compressed (8–13:1 ratio typical)
• Two tiers:
  • Best (zstd -9 + index strip + VACUUM INTO) — written on explicit index_repository
  • Fast (zstd -3) — written by the watcher for low-latency incremental updates
• Bootstrap: when no local DB exists but the artifact is present, index_repository imports the artifact first, then runs incremental indexing — avoiding the full reindex cost
• No merge pain: a .gitattributes line with merge=ours is auto-created on first export, so concurrent edits don't produce conflicts on the binary artifact
• Optional: never committed unless you want it. Add .codebase-memory/ to .gitignore if you prefer everyone to reindex from scratch.

The result is similar in spirit to graphify's graphify-out/ directory, but as a single compressed file with explicit two-tier export, integrity-checked import, and zero merge friction.

How It Works

codebase-memory-mcp is a structural analysis backend — it builds and queries the knowledge graph. It does not include an LLM. Instead, it relies on your MCP client (Claude Code, or any MCP-compatible agent) to be the intelligence layer.

You: "what calls ProcessOrder?"

Agent calls: trace_path(function_name="ProcessOrder", direction="inbound")

codebase-memory-mcp: executes graph query, returns structured results

Agent: presents the call chain in plain English

Why no built-in LLM? Other code graph tools embed an LLM for natural language → graph query translation. This means extra API keys, extra cost, and another model to configure. With MCP, the agent you're already talking to is the query translator.

Performance

Benchmarked on Apple M3 Pro:

RAM-first pipeline: All indexing runs in memory (LZ4 HC compressed read, in-memory SQLite, single dump at end). Memory is released back to the OS after indexing completes.

Token efficiency: Five structural queries consumed ~3,400 tokens via codebase-memory-mcp versus ~412,000 tokens via file-by-file grep exploration — a 99.2% reduction.

Troubleshooting & Diagnostics

codebase-memory-mcp runs 100% locally and collects no telemetry — your code, queries, environment, and usage never leave your machine. That privacy guarantee also means that when you hit something we can't reproduce on our side (a slow memory climb over hours, a performance regression, a leak that only appears after days of real use), we have no data at all unless you choose to send it. Here is how to capture it yourself.

Capture a diagnostics log

Set CBM_DIAGNOSTICS=1 before the MCP server starts, then reproduce the problem (let it run as long as it takes — a slow leak needs time to show in the trend). The server writes two files to your system temp directory ($TMPDIR or /tmp on macOS/Linux, %TEMP% on Windows):

The startup log prints both paths, e.g.:

level=info msg=diagnostics.start snapshot=/tmp/cbm-diagnostics-12345.json trajectory=/tmp/cbm-diagnostics-12345.ndjson interval=5s

Set the variable in the env block of your agent's MCP server config, or export it before launching the server.

What to share

When you open a memory/performance issue, attach the .ndjson trajectory — it contains no source code or query text, only resource counters. If you'd rather not attach a file, paste it (or an agent's summary of it) into the issue: your assistant can read the NDJSON directly and report whether rss/committed grow monotonically, how fast, and relative to query count — which is exactly what we need to find the cause.

Installation

Pre-built Binaries

Every release includes checksums.txt with SHA-256 hashes. All binaries are statically linked — no shared library dependencies.

Windows note: SmartScreen may show a warning for unsigned software. Click "More info" → "Run anyway". Verify integrity with checksums.txt.

Setup Scripts

macOS / Linux:

curl -fsSL https://raw.githubusercontent.com/DeusData/codebase-memory-mcp/main/scripts/setup.sh | bash

Windows (PowerShell):

irm https://raw.githubusercontent.com/DeusData/codebase-memory-mcp/main/scripts/setup-windows.ps1 | iex

AUR (Arch Linux)

yay -S codebase-memory-mcp-bin

paru -S codebase-memory-mcp-bin

The codebase-memory-mcp-bin package is available at: https://aur.archlinux.org/packages/codebase-memory-mcp-bin

Install via Claude Code

You: "Install this MCP server: https://github.com/DeusData/codebase-memory-mcp"

Build from Source

git clone https://github.com/DeusData/codebase-memory-mcp.git
cd codebase-memory-mcp
scripts/build.sh                    # standard binary
scripts/build.sh --with-ui          # with graph visualization
# Binary at: build/c/codebase-memory-mcp

Manual MCP Configuration

Add to ~/.claude/.mcp.json (global) or project .mcp.json:

{
  "mcpServers": {
    "codebase-memory-mcp": {
      "command": "/path/to/codebase-memory-mcp",
      "args": []
    }
  }
}

Restart your agent. Verify with /mcp — you should see codebase-memory-mcp with 14 tools.

Multi-Agent Support

install auto-detects and configures all installed agents:

Hooks are structurally non-blocking (exit code 0, every failure path). For Claude Code, the PreToolUse hook intercepts Grep/Glob (never Read — gating Read breaks the read-before-edit invariant) and, when the search token matches indexed symbols, injects them as additionalContext via search_graph so the agent gets structured context alongside its normal search results. For Codex, Gemini CLI, and Antigravity, a SessionStart hook injects a one-line code-discovery reminder as session context (Gemini CLI also keeps its BeforeTool reminder). The installed Claude shim file is named cbm-code-discovery-gate for backward compatibility with existing installs; despite the legacy name it never gates and never blocks.

CLI Mode

Every MCP tool can be invoked from the command line:

codebase-memory-mcp cli index_repository '{"repo_path": "/path/to/repo"}'
codebase-memory-mcp cli search_graph '{"name_pattern": ".*Handler.*", "label": "Function"}'
codebase-memory-mcp cli trace_path '{"function_name": "Search", "direction": "both"}'
codebase-memory-mcp cli query_graph '{"query": "MATCH (f:Function) RETURN f.name LIMIT 5"}'
codebase-memory-mcp cli list_projects
codebase-memory-mcp cli --raw search_graph '{"label": "Function"}' | jq '.results[].name'

MCP Tools

Indexing

Querying

Graph Data Model

Node Labels

Project, Package, Folder, File, Module, Class, Function, Method, Interface, Enum, Type, Route, Resource

Edge Types

CONTAINS_PACKAGE, CONTAINS_FOLDER, CONTAINS_FILE, DEFINES, DEFINES_METHOD, IMPORTS, CALLS, HTTP_CALLS, ASYNC_CALLS, IMPLEMENTS, HANDLES, USAGE, CONFIGURES, WRITES, MEMBER_OF, TESTS, USES_TYPE, FILE_CHANGES_WITH

Qualified Names

get_code_snippet uses qualified names: <project>.<path_parts>.<name>. Use search_graph to discover them first.

Supported Cypher (openCypher read subset)

query_graph is a read-only openCypher subset:

• Clauses: MATCH, OPTIONAL MATCH, multiple MATCH, WHERE, WITH (+ WITH … WHERE), RETURN, ORDER BY, SKIP, LIMIT, DISTINCT, UNWIND, UNION / UNION ALL, CASE.
• Patterns: labelled nodes, label alternation (n:A|B), relationship types/direction, variable-length paths [*1..3], inline property maps.
• WHERE: = <> < <= > >=, AND/OR/XOR/NOT, IN, CONTAINS, STARTS WITH, ENDS WITH, IS [NOT] NULL, regex =~, label test n:Label, and EXISTS { (n)-[:TYPE]->() } (single-hop existence — great for dead-code, e.g. WHERE NOT EXISTS { (f)<-[:CALLS]-() }).
• Aggregates: count (+DISTINCT), sum, avg, min, max, collect.
• Functions: labels, type, id, keys, properties; toLower/toUpper/toString/toInteger/toFloat/toBoolean; size, length, trim/ltrim/rtrim, reverse; coalesce, substring, replace, left, right.

Anything outside this subset (write/MERGE/CALL clauses, unsupported functions, list/map literals, comprehensions, path functions, parameters) fails with a clear unsupported … error rather than returning empty results.

Ignoring Files

Layered: hardcoded patterns (.git, node_modules, etc.) → .gitignore hierarchy → .cbmignore (project-specific, gitignore syntax). Symlinks are always skipped.

See docs/cbmignore.md for the full .cbmignore how-to: syntax, precedence across the ignore layers, and negation semantics.

Configuration

codebase-memory-mcp config list                          # show all settings
codebase-memory-mcp config set auto_index true           # auto-index on session start
codebase-memory-mcp config set auto_index_limit 50000    # max files for auto-index
codebase-memory-mcp config set auto_watch false          # don't register background git watcher (default: true)
codebase-memory-mcp config reset auto_index              # reset to default

Environment Variables

# Store indexes in a custom directory
export CBM_CACHE_DIR=~/my-projects/cbm-data

Custom File Extensions

The JSON config files support a single key, extra_extensions, which maps additional file extensions to supported languages. Useful for framework-specific extensions like .blade.php (Laravel) or .mjs (ES modules). (For other tunables, see Environment Variables and the config subcommand above.)

Need the full config-file reference? See docs/CONFIGURATION.md.

Per-project (in your repo root):

// .codebase-memory.json
{"extra_extensions": {".blade.php": "php", ".mjs": "javascript"}}

Global (applies to all projects):

// ~/.config/codebase-memory-mcp/config.json  (or $XDG_CONFIG_HOME/...)
{"extra_extensions": {".twig": "html", ".phtml": "php"}}

Each entry maps an extension (which must start with .) to a language name. Language names are matched case-insensitively. Accepted values (aliases in parentheses) are:

bash (sh), c, c++ (cpp), c# (csharp), clojure, cmake, cobol, common lisp (commonlisp, lisp), css, cuda, dart, dockerfile, elixir, elm, emacs lisp (emacslisp), erlang, f# (fsharp), form, fortran, glsl, go, graphql, groovy, haskell, hcl (terraform), html, ini, java, javascript, json, julia, kotlin, lean, lua, magma, makefile, markdown, matlab, meson, nix, objective-c (objc), ocaml, perl, php, protobuf, python, r, ruby, rust, scala, scss, sql, svelte, swift, toml, tsx, typescript, verilog, vimscript, vue, wolfram, xml, yaml, zig.

Project config overrides global for conflicting extensions. An entry whose language name is unknown, or whose extension does not start with ., is skipped and a warning is logged to stderr (shown at the default info log level). Missing config files are ignored.

Persistence

SQLite databases stored at ~/.cache/codebase-memory-mcp/. Persists across restarts (WAL mode, ACID-safe). To reset: rm -rf ~/.cache/codebase-memory-mcp/.

Troubleshooting

Hybrid LSP

Semantic type resolution beyond tree-sitter.

Tree-sitter alone gives a syntactic AST. That handles naming, structure, and call sites well, but it can't tell you that user.profile.display_name() resolves to Profile.display_name declared three modules away — tree-sitter doesn't track imports, generics, inheritance, or stdlib types.

codebase-memory-mcp ships a lightweight C implementation of language type-resolution algorithms, structurally inspired by and compatible with major language servers (tsserver / typescript-go, pyright, gopls, Roslyn, Eclipse JDT, rust-analyzer), embedded directly into the static binary. No language server process, no per-project setup, no API key. We call this layer Hybrid LSP: it runs alongside tree-sitter on every parse and refines CALLS, USAGE, and RESOLVED_CALLS edges with type information, so the resulting graph mirrors what an IDE "Go to Definition" would resolve.

Languages with full Hybrid LSP:

Two-layer architecture:

1. Tree-sitter pass — fast, syntactic, runs for every one of the 158 languages. Extracts definitions, calls, imports.
2. Hybrid LSP pass — type-aware, runs above the tree-sitter pass per-language. Refines call edges using the import graph plus a per-file or pre-built cross-file definition registry. Languages without a Hybrid LSP pass yet fall back to textual resolution, so you always get some answer.

The result is a knowledge graph accurate enough to drive trace_path across packages, inheritance hierarchies, and stdlib calls — without paying for a language server process per project.

Language Support

158 languages, all parsed via vendored tree-sitter grammars compiled into the binary. Benchmarked against 64 real open-source repositories (78 to 49K nodes):

Also supported (not yet benchmarked): Ada, Agda, Apex, Assembly (NASM), Astro, AWK, Beancount, BibTeX, Bicep, Bitbake, Blade, Cairo, Cap'n Proto, Clojure, CMake, COBOL, Common Lisp, Crystal, CSV, CUDA, D, Devicetree, Diff, .env, Elm, Emacs Lisp, F#, Fennel, Fish, FORM, Fortran, FunC, GDScript, .gitattributes, .gitignore, Gleam, GLSL, GN, Go module, Go template, GraphQL, Hare, HLSL, Hyprlang, INI, ISPC, Janet, Jinja2, JSDoc, JSON, JSON5, Jsonnet, Julia, Just, Kconfig, KDL, Lean 4, Linker Script, Liquid, LLVM IR, Luau, Magma, Makefile, Markdown, MATLAB, Mermaid, Meson, Move, Nickel, Nim, Nix, Odin, Pascal, Pkl, PO (gettext), Pony, PowerShell, Prisma, .properties, Protobuf, Puppet, PureScript, Racket, Regex, requirements.txt, ReScript, RON, reStructuredText, Scheme, Slang, Smali, Smithy, Solidity, SOQL, SOSL, Squirrel, SSH config, Starlark, Svelte, Sway, SystemVerilog, TableGen, Tcl, Teal, Templ, Thrift, TLA+, Typst, Verilog, VHDL, Vim script, Vue, WGSL, WIT, Wolfram, XML, Zsh.

Architecture

src/
  main.c              Entry point (MCP stdio server + CLI + install/update/config)
  mcp/                MCP server (14 tools, JSON-RPC 2.0, session detection, auto-index)
  cli/                Install/uninstall/update/config (10 agents, hooks, instructions)
  store/              SQLite graph storage (nodes, edges, traversal, search, Louvain)
  pipeline/           Multi-pass indexing (structure → definitions → calls → HTTP links → config → tests)
  cypher/             Cypher query lexer, parser, planner, executor
  discover/           File discovery (.gitignore, .cbmignore, symlink handling)
  watcher/            Background auto-sync (git polling, adaptive intervals)
  traces/             Runtime trace ingestion
  ui/                 Embedded HTTP server + 3D graph visualization
  foundation/         Platform abstractions (threads, filesystem, logging, memory)
internal/cbm/         Vendored tree-sitter grammars (158 languages) + AST extraction engine

Security

Every release binary is verified through a multi-layer pipeline before publication:

• VirusTotal — all binaries scanned by 70+ antivirus engines (zero detections required to publish)
• SLSA Level 3 — cryptographic build provenance generated by GitHub Actions; verify with gh attestation verify <file> --repo DeusData/codebase-memory-mcp
• Sigstore cosign — keyless signatures on all artifacts; bundles included in every release
• SHA-256 checksums — checksums.txt published with every release; verified by both install scripts before extraction
• CodeQL SAST — blocks release pipeline if any open alerts remain
• Zero runtime dependencies — no transitive supply chain; all libraries vendored at compile time

v0.7.0 VirusTotal scans

Scan links for every release are also included in the GitHub Release notes automatically.

License

MIT