iknowhy 0.4.1

Causal event capture for AI agents — with native PyRapide integration

iknowhy

Python SDK for iKnowhy.ai — the causal event intelligence platform.

Log every decision, tool call, and outcome your AI agent makes. Trace exactly why things happened. Surface violations. Build the audit trail automatically.

pip install iknowhy

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Claude Integration — One-Time Setup

iKnowhy natively integrates with Claude Code, Claude Desktop, and Claude.ai. After a single setup command, every Claude session logs causal events automatically — no prompting, no manual tool calls.

Step 1 — Get your API key

Sign up at iknowhy.ai → account dashboard → copy your cwy_... key.

Step 2 — Run setup

pip install iknowhy
iknowhy setup --key cwy_your_key_here

That's it. The setup command:

• ✅ Claude Code — registers iKnowhy as an MCP server in ~/.claude/mcp.json and writes auto-logging instructions to ~/.claude/CLAUDE.md. Every claude session from this point forward logs automatically.
• ✅ Claude Desktop — patches claude_desktop_config.json with the MCP server. Restart Desktop to activate.
• 📋 Claude.ai (web) — prints a ready-to-paste system prompt + connector URL for a one-time Project setup (see below).

Claude.ai Setup (one time)

Claude.ai custom connectors require a Pro, Max, Team, or Enterprise plan.

1. Go to claude.ai → Projects → New Project
2. Project Settings → Custom Instructions → paste the system prompt printed by iknowhy setup
3. Project Settings → Connectors → Add connector:
   • Name: iKnowhy
   • URL: https://iknowhy.ai/mcp?key=cwy_your_key
4. Enable the connector via the + button in any conversation in this project

Every conversation in this project auto-logs from that point forward.

Free tier: Claude.ai connectors are not available on the free plan. Claude Code and Claude Desktop work on all plans.

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MCP Server

iKnowhy runs a live remote MCP server at:

https://iknowhy.ai/mcp?key=cwy_your_key

Compatible with any MCP client (Claude Code, Claude Desktop, Claude.ai, and any app supporting MCP Streamable HTTP transport).

Tools exposed

Tool	Description
new_session	Start a named causal session. Returns session_id.
log_event	Log a causal event with name, session_id, payload, cause_ids, tags.
get_sessions	List recent sessions with event counts and durations.
get_chain	Trace the full causal ancestry of any event.
get_violations	Check for broken causal rules (e.g. tool_call with no tool_result).

Manual MCP registration (without the setup CLI)

Claude Code:

# Add to ~/.claude/mcp.json
{
  "mcpServers": {
    "iknowhy": {
      "type": "http",
      "url": "https://iknowhy.ai/mcp?key=cwy_your_key"
    }
  }
}

Claude Desktop — add to claude_desktop_config.json:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json
• Linux: ~/.config/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "iknowhy": {
      "type": "http",
      "url": "https://iknowhy.ai/mcp?key=cwy_your_key"
    }
  }
}

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Python SDK

For direct API access — log events from your own code, scripts, or agents.

from iknowhy import CausewayClient

client = CausewayClient(api_key="cwy_...")

# Start a session
session_id = "my-session-001"

# Log a causal chain
req  = client.log("user_request",  payload={"task": "analyze logs"},  session_id=session_id)
dec  = client.log("decision",      payload={"action": "run scan"},    session_id=session_id, cause_ids=[req])
call = client.log("tool_call",     payload={"tool": "scanner"},       session_id=session_id, cause_ids=[dec])
res  = client.log("tool_result",   payload={"findings": 3},           session_id=session_id, cause_ids=[call])
done = client.log("task_complete", payload={"status": "ok"},          session_id=session_id, cause_ids=[res])

# Trace why something happened
chain = client.chain(done)
for event in chain:
    print(event["name"], "←", event.get("cause_ids", []))

# Check for violations
violations = client.violations()
print(f"{len(violations)} constraint violations found")

CausewayClient reference

CausewayClient(api_key: str, base_url: str = "https://iknowhy.ai")

Method	Returns	Description
log(name, payload, session_id, cause_ids, tags)	str (event_id)	Log a causal event
chain(event_id)	list[dict]	Full causal ancestry for an event
violations(session_id)	list[dict]	Constraint violations
sessions(limit)	list[dict]	Recent sessions
events(session_id, name, limit)	list[dict]	Query events

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Standard Event Types

Use consistent names to get the most out of iKnowhy's causal analysis:

Event Name	When to use
user_request	User sends a message or task
decision	Agent chooses an approach
tool_call	Before calling any tool
tool_result	After receiving a tool result
error	Any failure or exception
error_handling	Recovery from an error
external_send	Sending output to external system
task_complete	Task finished

Always chain them: tool_result should have cause_ids=[tool_call_id].

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PyRapide Integration

iKnowhy integrates natively with PyRapide, the causal event-driven architecture library by Shane Morris.

pip install iknowhy pyrapide

Batch mode

from iknowhy import CausewayClient
from iknowhy.pyrapide import PyRapideAdapter

client = CausewayClient(api_key="cwy_...")
adapter = PyRapideAdapter(client, session_id="security-scan-001")

comp = await engine.run(arch, timeout=5.0)
event_ids = await adapter.flush_computation(comp)
print(f"Logged {len(event_ids)} events to iKnowhy")

Streaming mode

adapter = PyRapideAdapter(client, session_id="live-monitor")
adapter.attach_stream(processor, session_id="live-monitor")
# Events flow to iKnowhy in real time as they pass through PyRapide

PyRapideAdapter reference

Method	Description
flush_computation(comp, session_id, tags)	Upload a completed PyRapide Computation
attach_stream(processor, session_id, tags)	Hook into a live StreamProcessor
id_map()	PyRapide event.id → iKnowhy event_id mapping
clear()	Reset ID map between computations

PyRapide by Shane Morris — github.com/ShaneDolphin/pyrapide · pypi.org/project/pyrapide

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Links

• iKnowhy Dashboard
• Full API Docs
• GitHub
• PyRapide — by Shane Morris