Pikelet runs on your own machine — the client starts it, so there is no endpoint to ping. 290 installs a week from npm. Last commit 1 Nov 2026.
Search self-contained .pikelet knowledge artifacts over MCP — no vector DB, no embedding API.
We read the source, 22 h 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.
return spawnSync(npm.command, [...npm.args, ...args], { ...options, shell: npm.shell });
await fs.copyFile(path.join(PACKAGE_ROOT, 'templates', name), dest);
return skip(`only ${offTopicNegatives.length} off-topic negatives survived the overlap drop (need ${MIN_NEGATIVES})`);
results.innerHTML = body.results.map((row) => `
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 pikelet -- npx -y pikelet
{
"mcpServers": {
"pikelet": {
"command": "npx",
"args": [
"-y",
"pikelet"
]
}
}
}
[mcp_servers.pikelet]
command = "npx"
args = ["-y", "pikelet"]
{
"mcpServers": {
"pikelet": {
"command": "npx",
"args": [
"-y",
"pikelet"
]
}
}
}
{
"servers": {
"pikelet": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"pikelet"
]
}
}
}
Minimal RAG-over-a-corpus MCP retrieval: search_knowledge returns cited chunks. Local embeddings.
MCP memory server for AI coding assistants. Windows Service, ONNX embeddings, SQLite vector search.
Self-hosted memory for AI agents over MCP: knowledge graph, vectors, graph RAG, cited answers.
Persistent local AI memory. SQLite + FTS5 + vector search, knowledge graph. No cloud, no API keys.
AI-powered vector knowledge graph MCP server for agents. Supports add node, add edge, semantic node
MCP server for the xAI Grok API — chat, vision, search, and embeddings
Persistent memory and knowledge graph for AI assistants — keyword + vector + graph search.
Local Markdown search, navigation and editing via MCP, with optional vector embeddings.
Answers built from our own checks of this server.