Amdb

amdb

amdb turns your codebase into AI context — entirely on your machine.

amdb is a zero-runtime, single-binary code context MCP server with combined graph + vector retrieval. No code leaves the machine and no Node/Python runtime is required. Built for air-gapped environments, CI containers, and regulated industries where cloud-based codebase indexing is prohibited.

Install

cargo install amdb

Or download a static binary for Linux/macOS from the Releases page — no toolchain required.

Quickstart

amdb init .    # index the repo: AST parse + local embeddings, incremental
amdb serve     # expose the index as an MCP server over stdio

Done. Prefer a file instead of a server? amdb generate --focus "auth" writes a targeted context file to .amdb/.

Connect your editor

VSCode / Cursor — add .vscode/mcp.json to your project:

{
  "servers": {
    "amdb": {
      "command": "amdb",
      "args": ["serve"]
    }
  }
}

Claude Code:

claude mcp add amdb -- amdb serve

The server exposes three tools, all reading from the pre-built local index:

If no index exists the tools respond with an error asking you to run amdb init — the server never indexes on its own.

Demo

Real session, 1.0 seconds end-to-end (scripts/demo.sh):

$ amdb init .
 INFO Initializing amdb in: .
 INFO Scanning files in ....
 INFO Files: 35 unchanged, 0 changed, 0 added, 0 removed
 INFO Indexing 0 files using 12 threads...
 INFO Embedding calls: 0
 INFO Project indexed successfully at .

$ amdb serve
  MCP client calls amdb_get_symbol with {"name": "cosine_similarity"}

cosine_similarity — src/core/vector_store.rs:196
  signature:  fn cosine_similarity(a: &[f32], b: &[f32]) -> f64
  visibility: private
  called by:  search (src/core/vector_store.rs)
  calls:      iter, map, sqrt, sum, zip

Answer came from the local index. No network. No code left the machine.

To record the cast on a host with asciinema: asciinema rec -c "AMDB_BIN=./target/release/amdb ./scripts/demo.sh" demo.cast, then agg demo.cast demo.gif.

Benchmarks

Measured by benchmark.py against amdb's own source tree (31 files, 21,887 raw tokens). Full methodology and caveats in benchmark.md.

3 of 31 files are module-declaration files with no extractable symbols; they are not in the index and are excluded from the denominator, not silently counted.

Language support

Symbols and the call graph are extracted for all 16 grammars, but is_public and signature enrichment is AST-accurate for only three languages. The rest fall back to is_public = true and no signature — honest table below, so you know what you get:

How it works

amdb init parses every source file with Tree-sitter, extracts symbols and call edges, and embeds each symbol with a local fastembed model — content-hashed, so unchanged files are skipped entirely on re-runs. Everything lands in two SQLite files: a symbol/relationship store and a vector store. Retrieval combines exact name matching, cosine similarity over the vectors, and call-graph expansion, served over MCP stdio or written to a Markdown context file.

Comparison

Same fixture repo (amdb's own source), same five questions ("where is symbol X defined, and who calls it?"), all numbers actually measured by benchmark.py. We did not run competitor indexing tools, so none appear here; the baselines are a raw full-repo dump and a scripted grep-then-read-matched-files agent protocol.

On a 31-file repo, grep is genuinely competitive on tokens — amdb's edge at this scale is one structured call instead of 2–4, with signatures, visibility, and resolver-accurate caller/callee attribution instead of raw text. The token gap widens with repo size: the dump grows linearly, grep grows with match noise, amdb's focus output grows with the size of the relevant interface.

More

Daemon mode — amdb daemon watches the project and incrementally re-indexes on save, keeping the MCP answers fresh.

Focus depth — amdb generate --focus <query> --depth N expands context N call-graph hops from the matched files (default 1).

Configuration — optional amdb.toml in the project root:

db_path = ".database"
ignore_patterns = ["target", ".git", "node_modules", ".amdb", ".fastembed_cache", "__pycache__", ".database"]

AMDB_DB_PATH overrides db_path. Add .database/ and .amdb/ to your .gitignore.

Verbose — -v / --verbose on any command for debug logs.

Docker — the repo Dockerfile builds a slim image whose entrypoint is amdb serve, so the container speaks MCP over stdio immediately:

docker build -t amdb .
docker run --rm -v "$PWD:/workspace" --entrypoint amdb amdb init .
docker run -i --rm -v "$PWD:/workspace" amdb

The published ghcr.io/betaer-08/amdb:1.0.0 image predates the serve entrypoint — it runs bare amdb, so pass the subcommand explicitly: docker run -i --rm -v "$PWD:/workspace" -w /workspace ghcr.io/betaer-08/amdb:1.0.0 serve. Images published from the next tag serve by default.

Stability

amdb follows semantic versioning. 1.0.0 freezes the contract below; anything listed as covered changes only in a 2.0 release, and contract tests in tests/contract_test.rs fail loudly if it drifts.

Covered by the 1.0 promise:

• CLI — subcommands init, daemon, generate, serve; flags --focus/-f, --depth/-d, --verbose/-v; the optional path argument to init and daemon. Exit codes: 0 on success, 1 on unrecoverable error.
• MCP tools — exactly amdb_get_context, amdb_focus, amdb_get_symbol with their current input parameters. amdb_get_symbol responses keep every current field with its current type: file, name, kind, line, signature, is_public, callers[] (name, file), callees[] (name, file, resolution ∈ same-file | global-unique | unresolved). New fields and new resolution values may be added in minor releases; existing ones are never renamed, removed, or retyped.
• Config — amdb.toml keys db_path and ignore_patterns, and the AMDB_DB_PATH environment override. Unknown keys are ignored.
• Database upgrades — the index schema is versioned via PRAGMA user_version. Any database written by amdb ≥ 0.6 opens without error and migrates automatically; the next amdb init rebuilds whatever the migration invalidated. Deleting .database/ is a last-resort fallback, never a required upgrade step.
• Generated Markdown anchors — two things in generate output are stable for scripts: each indexed file gets a heading line of exactly ### <relative/path> (forward slashes, relative to the project root), and the dependency graph is a single fenced ```mermaid block containing graph TD; with --> edge lines.

Not covered (may change in any release):

• Every other detail of the Markdown layout: bullet and signature formatting, section ordering, mermaid node-id sanitization, header text.
• Log and progress text on stdout/stderr.
• The SQLite table layout and the vector-store file format (only automatic migration is promised, not the bytes).
• The benchmark harness (benchmark.py) and its output format.
• Internal Rust APIs — amdb is a binary crate; depending on its modules as a library is unsupported.

License

MIT. Bug reports and inquiries: [email protected]