jCodeMunch MCP runs on your own machine — the client starts it, so there is no endpoint to ping. 20 997 installs a week from pypi. Last commit 2 Nov 2026.
Retrieves code by symbol via tree-sitter, so an agent reads the function it needs, not the file.
We read the source, 23 h ago · rules 995398eba69f
A value the model can set ends up inside a file or shell call. That is not a flaw by itself — for a terminal server it is the job — but it is where things go wrong when it is not.
r = subprocess.run(
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.
if os.path.exists("/.dockerenv"):
result = subprocess.run(
const child = spawn(cmd, ["index-file", filePath], {
and not os.path.exists(os.path.join(cwd, file_path))
rc, out = run_budgeted(fmt, budget, shell=True)
ON DUPLICATE KEY UPDATE total_tokens = total_tokens + VALUES(total_tokens)
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
That is not a flaw by itself — but it is where things go wrong when it is not the job. We re-read this code on every release. Watch it and you hear from us the day another one appears.
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 jcodemunch-mcp -- uvx jcodemunch-mcp
{
"mcpServers": {
"jcodemunch-mcp": {
"command": "uvx",
"args": [
"jcodemunch-mcp"
]
}
}
}
[mcp_servers.jcodemunch-mcp]
command = "uvx"
args = ["jcodemunch-mcp"]
{
"mcpServers": {
"jcodemunch-mcp": {
"command": "uvx",
"args": [
"jcodemunch-mcp"
]
}
}
}
{
"servers": {
"jcodemunch-mcp": {
"type": "stdio",
"command": "uvx",
"args": [
"jcodemunch-mcp"
]
}
}
}
Local Tree-sitter code graph: surgical edit context for AI agents instead of full-file reads.
Deterministic code maps for AI agents: 7 tree-sitter tools for TS/JS/Py — map, find, function_body
Free live-app check by an AI agent. On request it fixes the code and tests the app again.
Parse code into Tree-sitter ASTs to see node kinds, field names, and positions
Human-to-AI code review bridge. Review UI in the browser, AI agents fix code via MCP.
Retrieval over the folder the session opened: files, search, read, code_pack, write_note.
The shell around your coding agent: a neuro-symbolic code graph with calibrated trust, via MCP.
Cut AI agent token costs 5-15x — routes only relevant code symbols instead of full files.
Answers built from our own checks of this server.