Code Context Engine runs on your own machine — the client starts it, so there is no endpoint to ping. 290 installs a week from pypi. Last commit 23 Aug 2026.
Index your codebase. AI searches instead of re-reading files. 94% token savings.
What the code does
We read the source, 19 h ago · rules 3dff92dd89df
What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.
result = subprocess.run(upgrade_cmd, capture_output=True, text=True)
for path in cache_dir.rglob("*.incomplete"):
".npmrc", ".pypirc", ".netrc",
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
This code can reach further than it looks
We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.
Connect this server
This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.
claude mcp add code-context-engine -- uvx code-context-engine{
"mcpServers": {
"code-context-engine": {
"args": [
"code-context-engine"
],
"command": "uvx"
}
}
}[mcp_servers.code-context-engine]
command = "uvx"
args = ["code-context-engine"]{
"mcpServers": {
"code-context-engine": {
"args": [
"code-context-engine"
],
"command": "uvx"
}
}
}{
"mcpServers": {
"code-context-engine": {
"args": [
"code-context-engine"
],
"command": "uvx"
}
}
}Alternatives to Code Context Engine
same job, measured the same wayPersistent, read-only codebase memory for Claude Code; ask it instead of re-reading files.
The shared AI context engine for git — save, search, and share the reasoning behind code changes.
MCP server bridging OpenGrok search engine with AI for instant context across massive codebases.
Local file search for AI agents — semantic + keyword indexing over your codebase.
Lint AI agent context files (CLAUDE.md, AGENTS.md, etc.) against your actual codebase
Save tokens while coding — your AI agent gets structured code context, not file dumps.
Scores your prompts against your real codebase — context-aware prompt intelligence
Cut AI agent token costs 5-15x — routes only relevant code symbols instead of full files.
Code Context Engine — questions
Answers built from our own checks of this server.