VelesDB Memory MCP server

<!-- NOTE: several phrasings/numbers below are pinned verbatim by docs/reference/promise-contract.json and checked by scripts/check-promise-contract.py. Moving or rewording a pinned line/table (e.g. benchmark figures, "54 REST endpoints", binary size) will break that gate silently — check the contract first. --> VelesDB One ~14 MB binary fuses vector + graph + columnar under a single query language — with an agent memory that shows its evidence and a deterministic context compiler that cuts your real, billed token spend. Local-first: nothing leaves the machine, no LLM and no API key in the memory path. Every number below links to a committed harness you can rerun. Quick start &bull; Proof &bull; Limitations &bull; Architecture &bull; Roadmap &bull; velesdb.com

Start here — three commands that work

pip install velesdb
curl -O https://raw.githubusercontent.com/cyberlife-coder/VelesDB/main/examples/python/hello_velesdb.py
python hello_velesdb.py

To search your own text instead of hand-written vectors, install the opt-in local adapter (pip install "velesdb[embed-sentence-transformers]") and run hellovelesdbtext.py; its first run downloads all-MiniLM-L6-v2.

Expected output, byte-for-byte (read the script — no server, no embedding model):

Query: "tech"
  score=1.000  Rust 1.89 release notes
  score=0.600  AI-generated jazz: the new wave
  score=0.000  Best ramen in Tokyo

Query: "tech + music"
  score=0.990  AI-generated jazz: the new wave
  score=0.707  Rust 1.89 release notes
  score=0.707  Miles Davis discography

An embedding model determines the vector dimension, while your similarity semantics determine the metric. Both are fixed when a collection is created; to change either, create a new collection and re-index your documents.

Give your agent a persistent memory — three more commands:

cargo install velesdb-memory                                    # the local MCP memory server
claude mcp add velesdb-memory -- ~/.cargo/bin/velesdb-memory    # any MCP client works
curl -L https://github.com/cyberlife-coder/VelesDB/releases/latest/download/velesdb-skills.tar.gz | tar -xz -C ~/.claude/skills/

No Rust toolchain? npm i @wiscale/velesdb-memory-node, or grab a prebuilt .mcpb bundle from the official MCP Registry (io.github.cyberlife-coder/velesdb-memory).

Shortened. The full README is on GitHub.