Field Ops is answering right now. Last checked 11 min ago. It exposes 4 tools.
AI agents hire a human to observe, log or film on site. Typed results, feasibility before payment.
Over the last week it answered 99.1% of our checks. We check every 15 minutes, so you hear about the next outage within the hour — not from your users.
Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 11 min ago.
claude mcp add field-ops --transport http https://field-ops.filnith.workers.dev/mcp
{
"mcpServers": {
"field-ops": {
"url": "https://field-ops.filnith.workers.dev/mcp"
}
}
}
[mcp_servers.field-ops]
url = "https://field-ops.filnith.workers.dev/mcp"
{
"mcpServers": {
"field-ops": {
"url": "https://field-ops.filnith.workers.dev/mcp"
}
}
}
{
"mcpServers": {
"field-ops": {
"url": "https://field-ops.filnith.workers.dev/mcp"
}
}
}
Read directly from the server with tools/list, grouped by what they act on.
If a tool disappears, we record the date.
capabilities
check_feasibility
mission_status
order
| URL | Transport | State | Latency | Checked |
|---|---|---|---|---|
| https://field-ops.filnith.workers.dev/mcp | streamable-http | answering | 172 ms | 11 min ago |
Webhook Ai tools for AI agents. Capabilities: validate webhook signature, log webhook event, replay
Forum open to registered AI agents: posts, comments, votes, and a shared agent-to-agent memory log.
AI agent observability for production traces, natural-language insights, and improvement loops.
Observability for AI apps: investigate traces, logs, LLM usage, replays and crashes; manage alerts.
Step-by-step observability for MCP agent workflows
Production observability for AI agents: search runs, read evaluations, acknowledge incidents.
Structured observability for AI agents. Trace steps, decisions, and errors. MCP server + CLI viewer.
Shared project wiki for AI agents: read and write pages, next actions, and activity logs over MCP.
Answers built from our own checks of this server.