Sergey Matyukhin

Corpus Hub contributor since 2026-10-22

Sergey Matyukhin's work was selected for the XERJ Corpus Hub, the open reference memory AI coding agents search before they write code. When an agent meets the same problem, it gets this implementation back as a worked example, with the author and the repository attached.

1corpus

0selected commits

6files

548lines

Totals across every corpus @Smaturus appears in; a commit selected for two corpora counts once. Files and lines count the selected commits; each corpus indexes the whole repository at its pinned commit.

What an agent can do with the 1c-mcp-rag-search corpus

Smaturus/1c-mcp-rag-search: Search for 1C (BSL code + configuration metadata) exposed to LLM agents via MCP: local e5/Chroma retrieval, global BM25 + RRF hybrid…

Look up how 1c-mcp-rag-search implements 1c, 1c-enterprise, bm25, with answers cited to file and line.
Answer from 1c-mcp-rag-search's real Python source instead of memory (AI, prompts and agents).

Example questions

How does 1c-mcp-rag-search implement 1c?
What does data do in 1c-mcp-rag-search?

Paste it into your AI agent. It clones the repo at the pinned commit and indexes it on your machine.

Search the GitHub repository Smaturus/1c-mcp-rag-search with XERJ (https://hub.xerj.org/corpus/smaturus--1c-mcp-rag-search).
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/Smaturus/1c-mcp-rag-search 1c-mcp-rag-search && git -C 1c-mcp-rag-search checkout 99469ffc18eb5a43e5b7c18755c7464b97f705e2
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./1c-mcp-rag-search --url http://127.0.0.1:9200 --prefix 1c-mcp-rag-search --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: MIT. Keep the copyright notice and credit the authors.

corpus smaturus--1c-mcp-rag-search · AI, prompts and agents
Related corpora: deepeval, fastmcp, sickn33/tidal-mcp, TensorLink-AI/Gnomon
AI search and retrieval with XERJ · Case study: reference coding for agents

Selected work

GitHub ★ 0

Smaturus/1c-mcp-rag-search

selected commit: 6 files · 548 lines · Python · data, tests, src/mcp_1c_homework

The corpus is the whole repository at the pinned commit, not only the files of the selected commit.

selected · in licence reviewcorpus smaturus--1c-mcp-rag-searchAIMIT1c1c-enterprisebm25chromadbevaluationmcp agreed 2026-10-22

Not installable yet: this corpus is not in the hub registry until its licence review passes, so xerj corpus add and xerj ask cannot fetch it. It becomes installable when this card says live in the hub.

[![XERJ Corpus Hub contributor](https://hub.xerj.org/contributors/Smaturus/badge.svg)](https://hub.xerj.org/contributors/Smaturus)

Included with the author's permission (email, 2026-10-22), under each repository's own licence, with attribution. Want it removed? Reply to the email or open an issue on xerj-org/xerj.