Stele Context — AI skill for Claude Code

Stele Context

**Persistent memory for AI coding agents. A zero-dependency MCP server that lets Claude Code, Claude Desktop, Cursor, and any MCP-compatible AI coding assistant remember your codebase between conversations — instead of re-reading every file from scratch.**

[](https://pypi.org/project/stele-context/) [](https://opensource.org/licenses/MIT) [](https://www.python.org/downloads/) [](https://github.com/IronAdamant/stele-context) [](https://github.com/IronAdamant/stele-context/actions)

The Problem: AI Agents Re-Read Everything

Every new conversation with Claude Code, Cursor, or any other LLM coding tool starts from zero. The agent re-reads the same files it read yesterday, burning thousands of tokens on code that hasn't changed. On a medium-sized project that's real money and real context-window space spent re-learning what the agent already knew.

Stele Context is a local context cache that fixes this: index once, then only pay for what actually changed.

What It Does

1. Indexes your project files once — code, docs, configs, even images and PDFs — into a local SQLite database
2. Detects file changes with an mtime+size fast path and SHA-256 verification — unchanged files cost zero re-reads
3. Returns a diff instead of the whole file when something did change — a 1-line edit in a 600-line file comes back as a ~60-token unified diff, not a 10,000-token re-read
4. Searches your codebase by meaning, keyword, or exact pattern — semantic code search, BM25, and token-budgeted grep in one tool
5. Maps how your code connects — a symbol graph for find-references, go-to-definition, a