LoopGrid MCP runs on your own machine — the client starts it, so there is no endpoint to ping. 107 installs a week from pypi. Last commit 25 Sep 2026.
MCP bridge for tamper-evident evidence around consequential AI and agent decisions.
Today is the operative word: we check LoopGrid MCP 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 loopgrid-mcp -- uvx loopgrid-mcp
{
"mcpServers": {
"loopgrid-mcp": {
"command": "uvx",
"args": [
"loopgrid-mcp"
]
}
}
}
[mcp_servers.loopgrid-mcp]
command = "uvx"
args = ["loopgrid-mcp"]
{
"mcpServers": {
"loopgrid-mcp": {
"command": "uvx",
"args": [
"loopgrid-mcp"
]
}
}
}
{
"servers": {
"loopgrid-mcp": {
"type": "stdio",
"command": "uvx",
"args": [
"loopgrid-mcp"
]
}
}
}
Optional settings from the registry entry, left out of the block above:
LOOPGRID_BASE_URL (Base URL of the LoopGrid service), LOOPGRID_SERVICE_KEY (Scoped LoopGrid service API key when authentication is enabled), LOOPGRID_WORKSPACE (LoopGrid workspace id).
Record AI decisions to a tamper-evident audit ledger from any MCP-compatible agent.
MUJ428 verifies intent and evidence before consequential AI-agent actions.
Decision memory for AI agents: record, revisit, and resolve consequential choices.
Tamper-evident decision audit trail and outcome-weighted memory for AI trading agents.
Product context for AI agents: evidence, opportunities, initiatives, and decisions.
Read-only MCP access to a local append-only evidence ledger for AI agent sessions.
Local mandate gate and proof trail for AI agents that take consequential actions.
Typed AI decisions for agents: classify, route, screen evidence, score and batch-label text.
Answers built from our own checks of this server.