loci MCP server

loci

<!-- mcp-name: io.github.3M1RY33T/loci -->

Scoped memory for coding agents. A router in front of two stores.

question ──▶ router ──▶ ┌── structure store   what calls what
             (no LLM)   └── episode store     what happened and why
                        └─▶ merged, cited answer   │
                            or ABSTAIN ────────────┘

Knowledge graphs hold structure but no prose, so they cannot answer why did the cookie get dropped. Verbatim-recall systems hold prose but no call graphs, so they cannot answer what calls runagentturn. Both make you name the namespace when you write.

loci decides the scope when you read. One question path serves "how does auth work here" and "have I solved this in any project" — only the size of the scope set changes.

The shape, in one picture

A street of independent shops. Each shop is one project — its own stock, its own books, nothing pooled in a shared warehouse. Each keeps two ledgers: what calls what, and what happened and why. They are read together or not at all.

Shops wear overlapping badges — yours, this client's, that vendor's, this monorepo's. A badge can cover shops at opposite ends of the street, which is why they are labels rather than a hierarchy.

You never walk the street yourself. You ask the dispatcher, who knows only which uncommon words are stocked where. They send you into at most three shops, or say nobody here carries that and name who might.

Each shop also hangs a signboard naming what it is — repository, package, command — and keeps a list of what it reaches for. Reading one against the other is how the street answers which of my shops buys from another, which no amount of asking the dispatcher ever could: that question is about the road between two shops, and the dispatcher only knows what is stocked inside them.

One thing the street still lacks: aisles inside a shop, so a word found in a test fixture does not count like the same word in shipped code.

The problem it solves

Put every project in one index and the largest one wins regardless of the question. Measured against a merged graph of ten real repositories:

That third row is the trap. Merged retrieval looks excellent whenever the answer happens to live in the largest corpus and collapses when it does not. It is the same failure in both directions, visible in only one.

Install

The distribution is loci-mem; the command, the import and the project are all loci. PyPI's loci is an unrelated outlier-detection package abandoned in 2018 — the same split as python-dateutil installing as dateutil.

pipx install loci-mem                 # routing + lexical search, one dependency
pipx install 'loci-mem[all]'          # + graphify, local embeddings, MCP server

The base install pulls numpy, and nothing else. Routing, BM25 and the char-gram matrix are a compiled Rust extension as of 0.6.0, so scikit-learn (and scipy behind it), rank-bm25 and joblib are gone. No torch, no vector database, no model download unless you ask for one.

Wheels are published for macOS, Linux and Windows; installing from the sdist builds from source and needs a Rust toolchain (1.75+).

Quickstart

Shortened. The full README is on GitHub.