Snapstate runs on your own machine — the client starts it, so there is no endpoint to ping. 36 installs a week from npm. Last commit 15 Apr 2026.
Persistent state for AI agent workflows. Save, resume, and replay multi-step workflows.
We read the source, 7 d ago · rules 995398eba69f
Found in continuous integration, deployment or infrastructure files, or in a neighbouring package of the same monorepo. None of this is installed when you add the server: it describes how the project is built and released. We list it because a leaked key in a build pipeline is still a real problem, but it is not something this server does on your machine.
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Today is the operative word: we check Snapstate every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.
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 snapstate -e 'SNAPSTATE_API_URL=<SNAPSTATE_API_URL>' -e 'SNAPSTATE_API_KEY=<SNAPSTATE_API_KEY>' -- npx -y snapstate-sdk
{
"mcpServers": {
"snapstate": {
"command": "npx",
"args": [
"-y",
"snapstate-sdk"
],
"env": {
"SNAPSTATE_API_KEY": "<SNAPSTATE_API_KEY>",
"SNAPSTATE_API_URL": "<SNAPSTATE_API_URL>"
}
}
}
}
[mcp_servers.snapstate]
command = "npx"
args = ["-y", "snapstate-sdk"]
env = { SNAPSTATE_API_URL = "<SNAPSTATE_API_URL>", SNAPSTATE_API_KEY = "<SNAPSTATE_API_KEY>" }
{
"mcpServers": {
"snapstate": {
"command": "npx",
"args": [
"-y",
"snapstate-sdk"
],
"env": {
"SNAPSTATE_API_KEY": "<SNAPSTATE_API_KEY>",
"SNAPSTATE_API_URL": "<SNAPSTATE_API_URL>"
}
}
}
}
{
"servers": {
"snapstate": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"snapstate-sdk"
],
"env": {
"SNAPSTATE_API_KEY": "<SNAPSTATE_API_KEY>",
"SNAPSTATE_API_URL": "<SNAPSTATE_API_URL>"
}
}
}
}
Put your own values in place of
<SNAPSTATE_API_URL> (SnapState API URL), <SNAPSTATE_API_KEY> (Your SnapState API key (starts with snp_)).
The author’s registry entry marks them as required.
MCP State Sidecar: durable state persistence for multi-agent AI workflows
Shared versioned state for multi-agent AI workflows
Workflow planner, wave dispatcher, persistent swarm memory, and deploy preflight for AI agents.
Multi-provider search broker for AI agents: 14 providers, 12-step extraction, retrieval workflows.
Step-by-step observability for MCP agent workflows
Agent Workflow Engine — multi-step MCP workflows with per-step directives and validation.
Durable agent-to-agent handoffs and shared scratchpad for multi-agent workflows.
Reusable prompt templates, multi-step workflow chains, and quality gates for any MCP client.
Answers built from our own checks of this server.