Getting Started with Zipf

Monitoring infrastructure for AI agents and teams — describe what to watch, agents patrol, scored signals delivered to your systems.

Use the dashboard, connect any AI agent via MCP, or build with the REST API.

Web UI

Create a Monitor

Describe what you want to watch in plain English. Zipf's AI agents will patrol your sources on the schedule you set and deliver signals when something changes.

  1. Navigate to /monitors and click New Monitor
  2. Describe your monitoring intent (e.g., “Track AI safety research papers from major labs”)
  3. Set a cadence — every 6 hours, daily, or weekly
  4. Optionally add notifications (email or Slack) and tags

Zipf assesses your intent for specificity and suggests improvements if it's too vague. You can also start from quick-start templates (Competitor Monitor, News Alert, Research Tracker, and more).

Your Feed

The Feed is your intelligence briefing. It aggregates results from all your monitors into a single prioritized view.

  • Bottom line — A one-sentence executive summary of the period
  • Findings by signal tier — Urgent, notable, and routine items grouped by importance
  • Summary tiles — New findings count, briefing topics, active monitors

Filter by scope (All / Mine) and time window (6h / 24h / 3d / 7d) to focus on what matters.

Signal Scores

Every execution gets a signal score (0–100) that measures how actionable the results are. Scores are grouped into four tiers:

ScoreTierMeaning
80–100UrgentStop condition met or major changes detected
50–79NotableMeaningful updates worth reviewing
20–49RoutineMinor updates, incremental changes
< 20NoiseNo real information gain

What drives the score: stop-condition match (+50), new results detected (+20), change rate (up to +15), recency (up to +15), and penalties for no-change or empty findings.

Monitor Detail

Click into any monitor to see its execution history. Each execution shows:

  • Signal dot with score and tier color
  • AI-generated headline summarizing what changed
  • Key findings with source citations and badges (New Updated Context)
  • Change chips showing net new, dropped, and change rate

AI Edits

Refine a monitor without recreating it. Type a plain-English instruction like “Focus more on pricing changes and exclude opinion pieces” and the system adjusts the monitor's behavior. Every edit is recorded in the change timeline.

Chronicle

Individual executions show what happened now. Chronicle answers the bigger question: what's been happening over time?

  • Narrative arc — Executive summary of the monitor's history and current phase
  • Signal curve — Time-series chart of signal scores across executions
  • Topic threads — Recurring themes with trajectory (rising, stable, fading)
  • Entity tracks — Companies, people, and products tracked across findings
  • Coverage assessment — Source diversity and potential blind spots

Access Chronicle from any monitor's detail page. Select a time window: 1 day, 7 days, 30 days, 90 days, or all time.

Tags & Collections

Tag monitors to group them (e.g., #competitive, #ai-research). Collection Chronicle provides cross-monitor analysis for a tag group — a unified briefing across all monitors in that category.

Notifications

Get alerts where you work:

  • Per-monitor — Email or Slack webhook when a patrol finds something above your suppression threshold
  • Suppression threshold — Critical (80+), Important (50+), Balanced (20+, default), or All
  • Global email digest — Scheduled briefing to your inbox (every 6 hours, daily, or weekly)

Enable the digest at Dashboard → Account → Notifications. It's the single best way to stay informed without checking the dashboard.

MCP — Compose with Any AI Agent

Quick Setup

Any MCP-compatible AI agent can create, manage, and consume Zipf monitors — Claude Code, Codex, Gemini CLI, Cursor, or your own agents. OAuth handles authentication. Open protocol, not locked to one platform.

Connect your AI assistant

Pick your client and run the one-line setup. OAuth handles auth automatically.

Command

OpenAI Codex CLI

Command

codex mcp add zipf --url https://api.zipf.ai/mcp

Runs the hosted MCP server and opens browser login.

Advanced: Manual JSON Config (optional)
MCP Configuration (for manual setup)
Most users won't need this — the one-line setup above is simpler
{
  "mcpServers": {
    "zipf": {
      "url": "https://api.zipf.ai/mcp"
    }
  }
}

What You Can Do

TaskMCP Tool
Get your briefingmonitors_digest
Create a monitormonitors_create
List monitorsmonitors_list
Get monitor detailsmonitors_get
View reportsmonitors_list_reports
Refine a monitormonitors_update (with edit)
See trends over timemonitors_chronicle
Get expansion suggestionsmonitors_expansion_recommendations
Check creditscredits_balance

Example Prompts

Paste these into your AI assistant after connecting Zipf:

Create a monitor that tracks AI safety research papers daily

Give me a briefing of what happened in the last 24 hours

Show me the chronicle for my competitive intelligence monitors over the last 30 days

Refine my NVIDIA monitor to focus more on data center GPU demand and exclude consumer gaming

Need help? Visit the MCP Integration Dashboard for guided setup and troubleshooting.

API

Get Your API Key

Create a token at Dashboard → Tokens, then set it as an environment variable:

Set environment variable
export ZIPF_API_KEY="wvr_your_token_here"

Quick Reference

EndpointWhat it doesCredits
POST /v1/workflowsCreate a monitor1–2/exec
POST /v1/searchesWeb search1–2
POST /v1/crawlsCrawl & extract1–2/page
POST /v1/asksDirect answers2–5
POST /v1/sessionsMulti-step research0 (container)

Example: Create a Monitor

POST /v1/workflows
1 credit/execution | 2 credits with NL stop condition
curl -X POST https://api.zipf.ai/v1/workflows \
  -H "Authorization: Bearer $ZIPF_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "AI Safety Research Monitor",
    "mode": "simple",
    "workflow_type": "search",
    "operation_config": {
      "query": "AI safety research breakthroughs 2026",
      "max_results": 20
    },
    "stop_condition": {
      "type": "natural_language",
      "description": "Stop when a major AI safety breakthrough is announced",
      "confidence_threshold": 0.8
    },
    "interval": "1 day",
    "max_executions": 100
  }'

Example: Search

POST /v1/searches
1 credit (basic) | 2 credits with reranking or suggestions
curl -X POST https://api.zipf.ai/v1/searches \
  -H "Authorization: Bearer $ZIPF_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "AI infrastructure startups 2026",
    "max_results": 10
  }'

Core Concepts

How Monitors Work

Describe what to watch in plain English. Zipf's AI agents patrol your sources on a schedule, detect meaningful changes, and deliver structured signals when something matters. Each execution gets a headline, key findings, extracted fields, and a signal score.

Signal Scoring (0–100)

Every execution gets an information gain score. Not binary relevant/irrelevant — a quantified measure of how much new, actionable information was found. Scores drive feed ordering, notification suppression, and delivery routing.

Credits

Basic operations cost 1 credit. AI-enhanced features (reranking, extraction, NL conditions) cost 2. The Ask API ranges from 2–5 depending on depth. 100 free credits/month to start.

Next Steps

  1. Create your first monitorGo to Monitors and describe what to watch
  2. Enable the daily digestAccount → Notifications, turn on email digest
  3. Tag your monitors — Group related monitors for Collection Chronicle
  4. Check Chronicle after a week — See the narrative view of what your monitors found
  5. Refine with AI edits — Sharpen focus based on what you see

100 free credits/month. No credit card required.

Get Started
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Getting Started | Zipf AI