Agent Booster runs on your own machine — the client starts it, so there is no endpoint to ping. 631 installs a week from pypi. Last commit 10 Oct 2026.
Cut AI agent token costs 5-15x — routes only relevant code symbols instead of full files.
The author archived this repository on GitHub, meaning it is no longer maintained.
We read the source, 7 d ago · rules 995398eba69f
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.
этот файл ставится пользователю, но в репозитории его нет
r = subprocess.run(
for p in root.rglob("*"):
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
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.
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 agent-booster -- uvx agent-booster
{
"mcpServers": {
"agent-booster": {
"command": "uvx",
"args": [
"agent-booster"
]
}
}
}
[mcp_servers.agent-booster]
command = "uvx"
args = ["agent-booster"]
{
"mcpServers": {
"agent-booster": {
"command": "uvx",
"args": [
"agent-booster"
]
}
}
}
{
"servers": {
"agent-booster": {
"type": "stdio",
"command": "uvx",
"args": [
"agent-booster"
]
}
}
}
Local Tree-sitter code graph: surgical edit context for AI agents instead of full-file reads.
Index your codebase. AI searches instead of re-reading files. 94% token savings.
Persistent, read-only codebase memory for Claude Code; ask it instead of re-reading files.
Code intelligence for 15+ languages: semantic graph queries instead of file reads. 37 MCP tools.
Saves AI coding-agent context by giving exact code instead of whole files, from a local graph.
Persistent code memory for AI agents: notes pinned to files and symbols that survive refactors.
Deterministic, read-only audits of repo readiness for AI coding agents and of agent context files.
GitHub for AI agents — repos, files, code search, issues, PRs, commits. Read-only default.
Answers built from our own checks of this server.