# Cymatix Context: local-first context for LLM agents

Apache-2.0 · Python

An OpenAI-compatible proxy and MCP server over a persistent SQLite knowledge store. Point your client at it, and each turn it:

- weighs, then retrieves your codebase and documents into the context window
- runs no model inference on the default retrieval path
- stamps every context packet with a know/miss contract

```
$ pip install cymatix-context
$ cymatix ingest ./docs --recursive
$ cymatix query "what changed in the retrieval path?"
```

Receipts: [EnterpriseRAG-Bench leaderboard](https://huggingface.co/spaces/onyx-dot-app/EnterpriseRAG-Bench-Leaderboard) (v0.6.4 submission)

## Retrieve

- FTS5 lexical search widened by tags, synonyms, and co-activation
- Fully algorithmic by default: never waits on a model

## Deliver

- Assembles to a hard token budget
- Skips what a session already received, so context stays lean over turns

## Calibrate

- Every packet answers: know, with a confidence, or miss, with a reason
- Agents can trust what they got, or refresh it

## Surfaces

- **Proxy**: transparent. An OpenAI client points at `/v1/chat/completions` and context rides in with the request; the know/miss verdict is applied inside the pipeline before anything ships upstream
- **MCP + CLI**: explicit. Claude Code tools and `cymatix query` hand the context back to the caller, know/miss block attached
- **Agents**: `/context/packet` returns the agent-grade form: verified evidence, stale-risk flags, and refresh targets to act on

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Source: <https://cymatixcontext.com/>  
Agent index: <https://cymatixcontext.com/llms.txt> · Sitemap: <https://cymatixcontext.com/sitemap.xml>