vvooki-sys /

loomem

Open-source context layer for LLM agents: a single Rust binary served over MCP that feeds Claude, ChatGPT, Codex or any MCP client the…

A new way for AI to search for data
View on GitHub
4GitHub stars

Rust, Python

What XERJ indexed

Snapshot

Whole repository

The whole repository at commit fdb1dae31d (2026-10-25).

Selected work

vvooki
@vvooki-sys

“enforce fragment dates and finalize search evidence”. 9 files, 889 lines in loomem-server, bench.

Licence

The repository

Apache-2.0

LICENSE file checked at the pinned commit; the author agreed to inclusion.

The XERJ corpus

Apache-2.0, with credit

The author agreed by email on 2026-10-27. Same terms as the repository. Answers name the repo, the commit and the file:line.

selected for the XERJ Corpus Hublicence clearedsuggested use: adapt with attribution

ai-agentsembeddingsllmlocal-firstmcpmemoryrustagent-memory

Example questions

The prompt

Paste it into your AI agent. It clones vvooki-sys/loomem at the pinned commit and indexes it on your machine.

Search the GitHub repository vvooki-sys/loomem with XERJ (https://hub.xerj.org/corpus/vvooki-sys--loomem).
Run these in a shell, in order, and check each result before the next:
1. xerj --help  (success: it prints usage). If xerj is missing: curl -fsSL https://xerj.org/get | sh
2. git clone https://github.com/vvooki-sys/loomem loomem && git -C loomem checkout fdb1dae31dc9d9b074bafb9518592ab332edc4e2
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./loomem --url http://127.0.0.1:9200 --prefix loomem --progress plain
5. xerj autoindex map --url http://127.0.0.1:9200
Then answer my question from the indexed files and cite the ax_path of every hit. Query syntax: https://xerj.org/llms.txt
Licence: Apache-2.0. Keep the copyright notice and credit the authors.

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Selected work and consent: the XERJ registry.