About Yams
Yams is an MCP server published by trvon in the AI category: persistent memory for LLMs and apps. Content-addressed storage with dedupe, compression, full-text and vector search. It has been installed 0 times through Conduid.
The repository has 365 stars and 9 forks, with the last commit 6 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues (0) before depending on it in production.
Install
npx yamsThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
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Releases
README
[!WARNING] Experimental — not production ready. Expect bugs and breaking changes until 1.0.
Features
- SHA-256 content-addressed storage with block-level dedupe (Rabin chunking)
- Full-text search (SQLite FTS5) + semantic vector search (embeddings)
- Tree-sitter symbol extraction for 18 languages (list)
- Snapshot management with Merkle tree diffs and rename detection
- WAL-backed durability, high-throughput I/O, thread-safe
- CLI, MCP server, and C-ABI plugins (ONNX/GLiNER/ColBERT, S3 storage, PDF via ZYP)
- Interactive relevance tuning through CLI tuning and doctor workflows
Documentation
| Topic | Link |
|---|---|
| Install | docs/user_guide/installation.md |
| CLI reference | docs/user_guide/cli.md |
| MCP server | docs/user_guide/mcp.md |
| Embeddings | docs/user_guide/embeddings.md |
| Plugins | docs/PLUGINS.md |
| Build from source | docs/BUILD.md |
| Architecture | docs/architecture/ |
| Benchmarks | docs/benchmarks/README.md |
| Changelog | docs/changelogs/ |
| Roadmap | docs/roadmap.md |
Links
- SourceHut: https://sr.ht/~trvon/yams/
- GitHub mirror: https://github.com/trvon/yams
- Docs site: https://yamsmemory.ai
- Discord: https://discord.gg/rTBmRHdTEc
- License: GPL-3.0-or-later
Install
Supported: Linux x86_64/ARM64, macOS x86_64/ARM64, Windows x86_64.
# macOS
brew install trvon/yams/yams
# Docker
docker pull ghcr.io/trvon/yams:latest
# Debian/Ubuntu, Fedora/RHEL, Windows: see installation guide
Full install matrix and package repos: docs/user_guide/installation.md.
Build from source
./setup.sh Release # Linux/macOS (auto-detects toolchain, runs Conan + Meson)
meson compile -C build/release
./setup.ps1 Release # Windows
meson compile -C build/release
Requires a C++20 toolchain (GCC 13+, Clang 16+, or MSVC 2022+ recommended), Meson, Ninja, CMake, pkg-config, and Conan. See docs/BUILD.md.
Quick Start
yams init # interactive; use --auto for headless
yams add ./README.md --tags docs
yams add src/ --recursive --include="*.cpp,*.h" --tags code
yams search "config file" --limit 5
yams grep "TODO" --include="*.cpp"
yams list --limit 20
yams get <hash> -o ./output.bin
Shell completions: yams completion bash|zsh|fish|powershell. Install instructions: docs/user_guide/cli.md#cmd-completion.
MCP Server
YAMS ships an MCP server over stdio (JSON-RPC) for AI assistants.
yams serve
{
"mcpServers": {
"yams": { "command": "yams", "args": ["serve"] }
}
}
Tool reference and MCP client setup: docs/user_guide/mcp.md.
Plugins
yams plugin list # loaded plugins
yams plugin trust add ~/.local/lib/yams/plugins # trust a directory
yams plugin health # status
yams doctor plugin onnx # diagnose
Plugin architecture, trust model, and bundled plugins (ONNX, S3, ZYP, GLiNER, symbol extractor): docs/PLUGINS.md.
GPU acceleration (ONNX)
| Platform | Provider | Hardware |
|---|---|---|
| macOS | CoreML | Apple Silicon Neural Engine + GPU |
| Linux | CUDA | NVIDIA GPUs |
| Linux | MIGraphX | AMD GPUs (ROCm) |
| Windows | DirectML | Any DirectX 12 GPU (NVIDIA, AMD, Intel) |
Auto-detected at build. Override with YAMS_ONNX_GPU=auto|cuda|coreml|directml|migraphx|none. Details: plugins/onnx/README.md.
Simeon backend
YAMS uses simeon by default for both dense vector embeddings and lexical (BM25) search — no model download required. Set embeddings.backend = "simeon" in your TOML config (or leave it unset; simeon is the default). Fine-grained knobs live under [embeddings.simeon].
Simeon research now points to a practical ceiling-closing path for YAMS: pair retrieval with corpus adapters that expose structure the generic vector backend cannot infer alone — file paths, titles, sections, headings, issue IDs, citations, or domain-specific anchors. English ArguAna experiments moved from ~0.32 nDCG@10 with BM25 to ~0.76 with a topic adapter, while schema diagnostics showed the remaining headroom is structure recognition rather than more vector similarity.
YAMS now exposes this as a first-class search component: implement
yams::search::CorpusAdapter, register it with SearchEngine::addCorpusAdapter(),
or rely on the built-in YamsNativeCorpusAdapter for path-fragment and
agent-memory metadata queries such as pbi=PBI-043 task=list-json-refresh.
The native adapter uses English-first query seeding: it breaks natural-language
requests into compact content/path fragments, keeps structured tokens such as
docs/research or PBI-043, and records adapter_us, seed_count, and
path_seed_queries in debug metadata for profiling. The component is enabled
by default with SearchEngineConfig::enableCorpusAdapters and fused as
corpus_adapter evidence.
PRs are welcome for qrel-backed English corpora, yams-specific corpus adapters, and language/profile contributions that make this retrieval path testable beyond the current research fixture.
Full config reference and dim tradeoffs: docs/user_guide/embeddings.md.
Troubleshooting
yams doctor # full diagnostics
yams stats --verbose # storage statistics
yams repair --all # repair common issues
Build issues: docs/BUILD.md. Empty yams plugin list? Add a trust path: yams plugin trust add ~/.local/lib/yams/plugins.
Cite
@misc{yams,
author = {Trevon Williams},
title = {YAMS: Content-addressable storage with semantic search},
year = {2025},
publisher = {GitHub},
url = {https://github.com/trvon/yams}
}
README mirrored from the source repository 5 days ago. The original is authoritative.