Jev Filter runs on your own machine — the client starts it, so there is no endpoint to ping. 10 installs a week from npm. Last commit 24 Oct 2026.
Read-only semantic filtering, code search, log triage and traceable evidence for AI agents.
We read the source, 23 h ago · rules 995398eba69f
Things with no honest explanation: a promise that contradicts the code, code that runs at install time while hiding what it does, data leaving the machine.
self.process = subprocess.Popen(
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.
self.process = subprocess.Popen(
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
Code changes quietly between releases, and nobody reads the diff of a dependency. We do, on every release — watch Jev Filter and you get told the day something new turns up.
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 jev-filter -e 'TYPESAFE_API_KEY=<TYPESAFE_API_KEY>' -- npx -y @apixly/jev-filter
{
"mcpServers": {
"jev-filter": {
"command": "npx",
"args": [
"-y",
"@apixly/jev-filter"
],
"env": {
"TYPESAFE_API_KEY": "<TYPESAFE_API_KEY>"
}
}
}
}
[mcp_servers.jev-filter]
command = "npx"
args = ["-y", "@apixly/jev-filter"]
env = { TYPESAFE_API_KEY = "<TYPESAFE_API_KEY>" }
{
"mcpServers": {
"jev-filter": {
"command": "npx",
"args": [
"-y",
"@apixly/jev-filter"
],
"env": {
"TYPESAFE_API_KEY": "<TYPESAFE_API_KEY>"
}
}
}
}
{
"servers": {
"jev-filter": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@apixly/jev-filter"
],
"env": {
"TYPESAFE_API_KEY": "<TYPESAFE_API_KEY>"
}
}
}
}
Put your own value in place of
<TYPESAFE_API_KEY> (Your TypeSafe Jev API key. Inference calls are billable; do not publish the key).
The author’s registry entry marks it as required.
Research intelligence for AI coding agents. 2M+ CS papers with evidence and tradeoffs.
Hybrid semantic and keyword code search for coding agents.
Local file search for AI agents — semantic + keyword indexing over your codebase.
Semantic code search and analysis from CodeAlive for AI assistants and agents.
Local code search for AI coding agents: hybrid keyword + semantic + SQL over an index in your repo.
Fast semantic code search for AI agents — find symbols, references, and callers across any codebase
Efficient context management: code search, evidence packs, and memory for coding agents.
Deterministic repo map, search and file reader for AI agents.
Answers built from our own checks of this server.