Introduction

Code Context Engine (CCE) is a local MCP server that indexes your codebase so AI coding agents search for relevant code instead of reading entire files.

The problem

Every time an AI agent needs to understand your code, it reads entire files. A 500-line file costs 500 lines of input tokens even when the agent only needs one function. Across a session, this adds up to thousands of wasted tokens and real dollars.

The solution

CCE parses your code into semantic chunks (functions, classes, modules) using Tree-sitter, stores them with vector embeddings, and serves only the relevant pieces when the agent asks a question.

Result: 94% input token savings, reproducibly benchmarked.

What you get

Tool	Purpose
context_search	Hybrid vector + keyword search with graph expansion
get_chunk	Retrieve a specific chunk by ID
record_decision	Store architectural decisions for cross-session recall
record_code_area	Mark areas you’ve worked on
session_recall	Recall decisions and code areas
session_timeline	Browse tool call history
session_event	Inspect a specific past event
set_output_level	Control output compression (off/lite/standard/max)
set_scope	Limit search to specific directories

Supported agents

Editor	Config written	Instructions
Claude Code	.mcp.json	CLAUDE.md
VS Code / Copilot	.vscode/mcp.json	.github/copilot-instructions.md
Cursor	.cursor/mcp.json	.cursorrules
Gemini CLI	.gemini/settings.json	GEMINI.md
OpenAI Codex	~/.codex/config.toml	AGENTS.md
OpenCode	opencode.json
Tabnine	.tabnine/agent/settings.json	TABNINE.md

How it works

1. Index — Tree-sitter parses code into semantic chunks. Stored locally with vector embeddings.
2. Search — Agent calls context_search via MCP. Hybrid vector + BM25 merged with Reciprocal Rank Fusion. Graph expansion adds related imports.
3. Compress — Chunks are compressed (truncation or LLM summary with Ollama). Session-wide output compression rules in instruction files reduce reply tokens (diff-only code, no filler).
4. Track — Every query recorded. cce savings shows tokens and dollars saved.