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**Stop wiring six MCP servers.** Argyph is one local binary that gives your AI coding agent grep, a symbol graph, and semantic search over any repo — indexed in under a second, with no API key.
[Install](#-install) · [Quick start](#-quick-start) · [How it works](#-how-it-works) · [Tools](#-tools) · [Architecture](ARCHITECTURE.md) · [Roadmap](ROADMAP.md)
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---
Most developers stitch together a half-dozen MCP servers to give an AI agent context over a codebase — one for grep, one for embeddings, one for symbol search, one for repo packing. Each is a separate install, a separate process, and (often) a separate cloud account. Argyph replaces all of them with a single local binary. It indexes incrementally and is ready in under a second on previously-indexed repos — no daemon, no account, no API key.
> The name is a portmanteau of **Argus** (the hundred-eyed watcher of Greek myth) and **Glyph** (a carved symbol with bound meaning) — a server that watches a codebase and gives the agent its symbols.
## ✨ What it does
Argyph exposes three pillars of context behind one MCP endpoint:
| Pillar | What you get |
|--------|--------------|
| 🧭 **Ask-first retrieval** | `ask` is the primary agent-facing lookup tool. It routes bare identifiers to symbol search, structured locators to `locate`, and natural-language questions to hybrid search — returning bounded `Span` results instead of whole files. |
| 🔗 **File & symbol intelligence** | A tree-sitter-driven symbol graph with `find_definition`, `find_references`, callers, callees, imports, and outline tools. Structural queries return in milliseconds. |
| 🧠 **Semantic search** | Hybrid (BM25 + vector) search over AST-aware chunks, backed by an embedded LanceDB store. A bundled local embedding model means no API key is required for full functionality. |
| 📦 **Repo packing** | Token-budgeted, repomix-style flattening of a repo or subset for agents that need to absorb a codebase quickly. |
> [!NOTE]
> Everything is **read-only**. Argyph never edits, commits, or executes code.
**Local-first by design.** Every tier runs on the developer's machine — your proprietary code never touches a cloud vector DB or a remote embedding API, and a bundled embedding model means full functionality with zero keys.
Why local-first?
Most existing context servers depend on a cloud vector database (Milvus, Pinecone) and a remote embedding API. That's a non-starter for proprietary code at most companies, and a tax on cold starts everywhere else.
Argyph runs entirely on the developer's machine: a single binary, an embedded vector store, an optional bundled embedding model — no daemon, no account, no key required to get full functionality.
## 📥 Install
> Current release: **`v1.0.4`** — published on npm, crates.io, the Homebrew tap, and as prebuilt GitHub-release binaries.
**Claude Code** (recommended):
```bash
claude mcp add argyph -- npx argyph@latest
```
**npm / npx:**
```bash
npx argyph
```
More install methods — Homebrew · universal installer · Cargo · source · Claude Desktop
### Homebrew (macOS / Linux)
```bash
brew install Ezzy1630/argyph/argyph
```
### Universal installer
```bash
curl -fsSL https://raw.githubusercontent.com/Ezzy1630/argyph/main/scripts/install.sh | bash
```
> **Intel Mac (`x86_64-apple-darwin`) users:** the ONNX Runtime backend
> doesn't ship a prebuilt for Intel macOS, so no prebuilt binary is
> produced for that target. Use the **Cargo** path below — it builds
> in a couple of minutes and works fine on Intel Macs.
### Cargo
`cargo install argyph` builds Argyph from source. Requires a **Rust
toolchain ≥ 1.88** (`rustup update`). The bundled local embedder uses
[`ort`](https://crates.io/crates/ort) (ONNX Runtime); on most
platforms `ort` ships a prebuilt dynamic library and there is nothing
to do. On Linux you may need `libssl-dev` and a working C toolchain;
on Windows the MSVC build tools are required. If the build fails on
`ort-sys` linkage, set `ORT_STRATEGY=download` before re-running.
```bash
cargo install argyph --locked
```
### Build from source
```bash
git clone https://github.com/Ezzy1630/argyph.git
cd argyph
cargo build --release
./target/release/argyph serve
```
### Claude Desktop (DXT)
Download `argyph.dxt` from the [latest release](https://github.com/Ezzy1630/argyph/releases/latest) and double-click.
## 🚀 Quick start
```bash
# In any repo
cd ~/code/your-repo
argyph init
claude mcp add argyph -- npx argyph@latest
claude
```
In the chat:
> *What does this codebase do, and where is session expiration controlled?*
Behind the scenes the agent calls `ask`, and Argyph returns bounded spans — not whole files — so the agent reads only what matters:
```json
{
"spans": [
{
"file": "src/auth/session.rs",
"start_line": 41,
"end_line": 55,
"text": "fn is_expired(&self, now: Instant) -> bool { ... }",
"kind": "definition",
"symbol": "is_expired",
"language": "rust"
}
],
"strategy_used": "definition"
}
```
Argyph indexes Tier 0 in under a second on first run, Tier 1 (symbol graph) in seconds, and Tier 2 (embeddings) in the background. You can query immediately — tools return what's available now plus an `index_coverage` field so the agent knows.
## ⚙️ How it works
Argyph builds the index in three tiers, each useful before the next completes:
| Tier | What it builds | Time on a 1M-LOC repo | Useful for |
|:----:|-----------------------------------------------|:---------------------:|------------------------------------------|
| 0 | File inventory, hashes, .gitignore-aware tree | <1 s | Tree views, ripgrep, packing |
| 1 | Symbol graph (defs, refs, calls, imports) | ~30 s | Go-to-def, find-references, call graphs |
| 1.5 | Structural index (non-code: md, json, yaml…) | seconds (after Tier 1)| `locate` for structured non-code files |
| 2 | Embeddings + hybrid index | minutes (background) | Fuzzy semantic queries |
The 80/20 insight: most agent queries are structural (`where is parseConfig defined?`, `what calls validateUser?`) and don't need embeddings. Argyph serves those from Tier 1 in milliseconds, even while Tier 2 is still building.
After the first index, the on-disk `.argyph/` directory persists and only changed files are reprocessed on subsequent runs. A filesystem watcher keeps everything live.
## 🧰 Tools
19 tools across 4 tiers
| Tool | Description | Tier required |
|-----------------------|----------------------------------------------------------|:-------------:|
| `ask` | Primary lookup router returning bounded spans | 0/1/1.5/2 |
| `get_index_status` | Tier readiness, embedding progress, watcher state | 0 |
| `get_repo_overview` | Languages, entry points, README excerpt, tree | 0 |
| `search_text` | Ripgrep-style regex / literal search | 0 |
| `find_definition` | Locate the definition of a named symbol | 1 |
| `find_references` | Reference sites with surrounding context | 1 |
| `get_callers` | Functions that call a given function | 1 |
| `get_callees` | Functions a given function calls | 1 |
| `get_imports` | Imports of a file, and files that import it | 1 |
| `get_symbol_outline` | Hierarchical outline of a file | 1 |
| `search_semantic` | Hybrid BM25 + vector over AST-aware chunks | 2 |
| `pack_repo` | Token-budgeted repo flattening (XML or markdown) | 0+1 |
| `locate` | Smallest natural span containing the target | 1.5 |
| `locate_smart` | Retrieval subagent (opt-in; needs provider config) | 1.5 |
| `expand_span` | Expand one truncated span from a session handle | 0 |
| `memory_save` | Persist a memory entry under a scope | 0 |
| `memory_search` | FTS5 search over persistent memories | 0 |
| `memory_list` | List memories in a scope | 0 |
| `memory_forget` | Delete a memory entry by id | 0 |
Full schema reference: [docs/tools-reference.md](docs/tools-reference.md).
Optional: locate_smart — retrieval subagent
`locate_smart` is an opt-in tool that runs a bounded multi-step retrieval loop using an LLM provider. It's **disabled by default**; enable it in `.argyph/config.toml`:
```toml
[locate_smart]
enabled = true
provider = "openai" # or "anthropic" | "ollama"
model = "gpt-4o-mini"
# endpoint = "http://localhost:11434" # only for local providers
```
Or via env:
```bash
ARGYPH_LOCATE_SMART_ENABLED=1
ARGYPH_LOCATE_SMART_PROVIDER=anthropic
ARGYPH_LOCATE_SMART_MODEL=claude-haiku-4-5
```
When disabled, calls to `locate_smart` return `LOCATE_SMART_DISABLED` immediately and no provider keys are required.
Build with the smart feature:
```bash
cargo install argyph --features smart
```
Configuration
Config is layered (highest priority first): env vars, `.argyph/config.toml` in the repo, built-in defaults. A config file is never required.
```bash
ARGYPH_LOG=info
ARGYPH_EMBED_PROVIDER=local # local | openai | voyage
OPENAI_API_KEY=... # standard provider env vars
ARGYPH_DISABLE_WATCHER=true # for sandboxed environments
```
Install agent lookup instructions in `CLAUDE.md`, `AGENTS.md`, or `GEMINI.md`:
```bash
argyph init
```
## 🆚 Why Argyph (vs alternatives)
| Tool | Symbol graph | Semantic search | Local-first | Single install | Incremental |
|-----------------------------|:------------:|:---------------:|:-----------:|:--------------:|:-----------:|
| claude-context (Zilliz) | — | ✅ | — | ✅ | ✅ |
| GitNexus / CodeGraphContext | ✅ | — | — | — | — |
| repomix | — | — | ✅ | ✅ | — |
| Serena | ✅ | — | ✅ | ✅ | — |
| **Argyph** | **✅** | **✅** | **✅** | **✅** | **✅** |
> Argyph is the only one that's all five — symbol graph **and** semantic search, local-first, one install, incremental.
## 📊 Benchmarks
Full methodology and reproduction steps are in [`docs/benchmarks.md`](docs/benchmarks.md) — reproduce locally with `cargo bench --workspace`. Numbers below are the median of three runs on the reference hardware tagged `m4-air` (Apple M4 MacBook Air, 16 GB RAM, macOS 26) unless stated otherwise.
| Fixture | Files | LOC | Tier 0 cold | Tier 1 full |
|--------------------------------------|-------:|-------:|------------:|------------:|
| `BurntSushi/ripgrep` | 215 | ~52K | **71 ms**| **6.8 s** |
| `microsoft/TypeScript` (`src/`) | 709 | ~452K | **30 ms**| **8.2 s** |
| `microsoft/TypeScript` (whole repo) | 81,310 | ~2M | **2.1 s** | see note ↓ |
Hot-path micro-benchmarks & large-monorepo notes
### Hot paths (criterion, mean times)
| Bench | Mean | What it measures |
|-----------------------------|-----------|------------------------------------------------|
| `locate_parse_path_bare` | ~15 ns | Parsing a bare path locator |
| `locate_parse_path_heading` | ~18 ns | Parsing `path > Heading` locators |
| `locate_strategy_path_only` | ~19 ns | Strategy dispatch for path-only locator |
| `locate_strategy_scoped` | ~32 ns | Strategy dispatch for scoped query locator |
| `token_count_rust_file` | ~4.4 µs | `cl100k_base` tokenization of one source file |
| `walk_project_root` | ~244 ms | Full `walkdir` traversal of this repo |
### System-level
Reproduce via:
```bash
cargo run --release -p argyph-benches --bin system_bench -- /path/to/repo
```
**Tier 0 — the "useful immediately" gate — scales linearly and fast**
(81K files in 2.1 s). `search_text` and `pack_repo` are available the
moment Tier 0 is ready.
**Tier 1 (the symbol graph) is fast on normal-to-large repos.** Two
optimizations landed for v1.0: the within-file reference resolver was
rewritten from an O(symbols²) substring scan to one-pass hash-indexed
lookups (4.2× — TypeScript compiler source: 34.6 s → 8.2 s), and the
per-file symbol/chunk SQL writes are now batched. On *very* large
monorepos (the full 81K-file TypeScript repo, ~2M LOC) Tier 1 still
does not finish within 30 min — the residual cost is raw tree-sitter
parse volume across 79K files, which needs streaming/parallel indexing
(tracked in [ROADMAP.md](ROADMAP.md)). The server never blocks at any
scale: Tier-1 tools return `INDEX_NOT_READY` with a retry hint until
the graph is ready. Full data: [`docs/benchmarks.md`](docs/benchmarks.md).
## 🏗️ Architecture
Argyph is a Rust workspace of twelve focused crates with strict module ownership. The full architecture — including the Supervisor lifecycle, the three-tier indexing model, and per-crate responsibility boundaries — is documented in [ARCHITECTURE.md](ARCHITECTURE.md).
## 📦 Project status
**Stable.** `v1.0.x` is published on all channels. Active development continues against the milestones at the top of [ROADMAP.md](ROADMAP.md); the build plan is in [`docs/BUILD_PLAN.md`](docs/BUILD_PLAN.md).
## 🤝 Contributing
Argyph is built with substantial AI assistance, but human-architected and human-reviewed. Contribution guide and the (strict) AI agent rules are in [CONTRIBUTING.md](CONTRIBUTING.md). Commit conventions, including the project's attribution policy, are in [`docs/COMMIT_CONVENTIONS.md`](docs/COMMIT_CONVENTIONS.md).
## 👤 Author
Built by [Ezzy1630](https://github.com/Ezzy1630). See [AUTHORS.md](AUTHORS.md).
## 📄 License
[](#-license)
[](#cargo)
Dual-licensed under either of:
- MIT License ([LICENSE-MIT](LICENSE-MIT))
- Apache License 2.0 ([LICENSE-APACHE](LICENSE-APACHE))
at your option.