clyro

# Clyro SDK

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**Runtime governance for AI agents — prevent failures before they happen.**

One `pip install`, three tools:

| Component | What it does | CLI |
|-----------|-------------|-----|
| **SDK** | Wrap any Python agent with tracing, cost limits, loop detection, and policy enforcement | `clyro-sdk` |
| **MCP Wrapper** | Govern MCP tool calls in Claude Desktop, Cursor, and VS Code | `clyro-mcp` |
| **Claude Code Hooks** | Block destructive commands (rm -rf, DROP TABLE) in Claude Code sessions | `clyro-hook` |

## What is Clyro?

Clyro is a governance platform for AI agents. While most tools let you watch agents fail, Clyro stops failures before they happen — catching infinite loops, runaway costs, and policy violations in real time.

**Works fully offline.** No API key required. Install, wrap, and get governance immediately with local YAML policies. Optionally connect to Clyro Cloud for team dashboards, shared policies, and session replay.

The SDK is the integration layer: add `clyro.wrap()` to any Python agent and you get execution tracing, cost tracking, step limits, loop detection, and policy enforcement — all with zero changes to your agent logic. If the SDK encounters an error, it fails open — your agent keeps running.

## Features

- **Works offline**: Local mode with YAML policies — no cloud dependency
- **5 framework adapters**: LangGraph, CrewAI, Claude Agent SDK, Anthropic SDK, Generic
- **Prevention Stack**: Step limits, cost limits, loop detection, business logic guardrails
- **Policy enforcement**: 8 operators, block/allow/require_approval, per-rule fail-open
- **Cost tracking**: Automatic LLM cost calculation for OpenAI and Anthropic models
- **MCP governance**: JSON-RPC proxy for Claude Desktop, Cursor, VS Code
- **Claude Code hooks**: PreToolUse/PostToolUse governance for Bash, Edit, Write
- **Minimal dependencies**: 6 lightweight packages — no heavy ML frameworks, no vendor lock-in
- **Fail-open design**: SDK failures never break your agent

## Quick Start

### Installation

```bash
pip install clyro
```

### 1. SDK — Wrap any Python agent

```python
import clyro
from clyro import ClyroConfig, ExecutionControls

# No API key needed — runs in local mode automatically
wrapped = clyro.wrap(
    your_agent,
    config=ClyroConfig(
        agent_name="my-agent",
        controls=ExecutionControls(
            max_steps=50,
            max_cost_usd=2.0,
            enable_loop_detection=True,
            enable_policy_enforcement=True,
        ),
    ),
)

# Run normally — governance enforced, session summary printed at end
result = wrapped.invoke({"messages": [{"role": "user", "content": "Hello"}]})
```

### 2. MCP Wrapper — Govern MCP tool calls

```bash
# Create config
cat > mcp_governance.yaml << 'EOF'
policies:
  - name: block-dangerous-commands
    rules:
      - tool_name: Bash
        conditions:
          - field: command
            operator: contains
            value: "rm -rf"
        decision: block
        message: "Destructive command blocked"
EOF

# Wrap any MCP server
clyro-mcp wrap --config mcp_governance.yaml -- npx @modelcontextprotocol/server-filesystem /tmp
```

### 3. Claude Code Hooks — Govern Claude Code

```json
// In Claude Desktop settings.json
{
  "hooks": {
    "PreToolUse": [{
      "type": "command",
      "command": "clyro-hook evaluate"
    }]
  }
}
```

### Local YAML Policies

Create `~/.clyro/sdk/policies.yaml`:

```yaml
rules:
  - name: cost-cap
    action_type: llm_call
    conditions:
      - field: cost
        operator: max_value
        value: 5.0
    decision: block
    message: "Session cost exceeded $5.00 limit"

  - name: block-dangerous-tool
    action_type: tool_call
    conditions:
      - field: tool_name
        operator: equals
        value: "delete_database"
    decision: block
    message: "Database deletion not allowed"
```

### Connect to Cloud (optional)

```python
# Add API key to enable cloud features: dashboards, team policies, session replay
config = ClyroConfig(
    api_key=os.environ.get("CLYRO_API_KEY"),  # Get from clyro.dev
    agent_name="my-agent",
    controls=ExecutionControls(max_steps=50, max_cost_usd=2.0),
)
```

## Configuration

### Environment Variables

```bash
export CLYRO_API_KEY="your-clyro-api-key"
export CLYRO_ENDPOINT="https://api.clyro.dev"
export CLYRO_AGENT_NAME="my-agent"
export CLYRO_MAX_STEPS="50"
export CLYRO_MAX_COST_USD="10.0"
```

```python
from clyro import ClyroConfig

config = ClyroConfig.from_env()
clyro.configure(config)
```

### Programmatic Configuration

```python
from clyro import ClyroConfig, ExecutionControls

config = ClyroConfig(
    # Authentication
    api_key=os.environ.get("CLYRO_API_KEY"),
    endpoint="https://api.clyro.dev",

    # Agent identification
    agent_name="my-production-agent",

    # Execution controls
    controls=ExecutionControls(
        max_steps=50,
        max_cost_usd=5.0,
        loop_detection_threshold=3,
        enable_step_limit=True,
        enable_cost_limit=True,
        enable_loop_detection=True,
    ),

    # Local storage
    local_storage_path="~/.clyro/traces.db",
    local_storage_max_mb=100,

    # Sync settings
    sync_interval_seconds=5.0,
    batch_size=100,
    retry_max_attempts=3,

    # Behavior
    fail_open=True,
    capture_inputs=True,
    capture_outputs=True,
    capture_state=True,
)

clyro.configure(config)
```

## Execution Controls

### Step Limits

Prevent runaway agent executions:

```python
from clyro import ClyroConfig, ExecutionControls, StepLimitExceededError

config = ClyroConfig(
    controls=ExecutionControls(max_steps=10)
)

@clyro.wrap(config=config)
def my_agent():
    # Will raise StepLimitExceededError after 10 steps
    pass

try:
    my_agent()
except StepLimitExceededError as e:
    print(f"Agent exceeded {e.limit} steps")
```

### Cost Limits

Control LLM spending:

```python
from clyro import ClyroConfig, ExecutionControls, CostLimitExceededError

config = ClyroConfig(
    controls=ExecutionControls(max_cost_usd=1.0)
)

@clyro.wrap(config=config)
def my_agent():
    # Will raise CostLimitExceededError if cost exceeds $1.00
    pass

try:
    my_agent()
except CostLimitExceededError as e:
    print(f"Cost ${e.current_cost_usd:.4f} exceeded limit ${e.limit_usd:.2f}")
```

### Loop Detection

Detect infinite loops automatically:

```python
from clyro import ClyroConfig, ExecutionControls, LoopDetectedError

config = ClyroConfig(
    controls=ExecutionControls(
        loop_detection_threshold=3,  # Detect after 3 iterations
        enable_loop_detection=True
    )
)

@clyro.wrap(config=config)
def my_agent():
    # Will raise LoopDetectedError if same state repeats 3 times
    pass

try:
    my_agent()
except LoopDetectedError as e:
    print(f"Loop detected: {e.iterations} iterations")
    print(f"State hash: {e.state_hash}")
```

## Cost Tracking

Automatic cost calculation for LLM calls:

```python
from clyro import calculate_cost

# OpenAI response
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello"}]
)
cost = calculate_cost(response)
print(f"Cost: ${cost:.4f}")

# Anthropic response
response = anthropic.messages.create(
    model="claude-3-sonnet-20240229",
    messages=[{"role": "user", "content": "Hello"}]
)
cost = calculate_cost(response)
print(f"Cost: ${cost:.4f}")
```

## Model Selection

Get cost-optimal model recommendations:

```python
from clyro import ModelSelector

selector = ModelSelector()

# Get recommendation for classification task
recommendation = select

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