# Lyzr

```json
{
  "name": "Lyzr",
  "slug": "lyzr",
  "url": "https://composio.dev/toolkits/lyzr",
  "markdown_url": "https://composio.dev/toolkits/lyzr.md",
  "logo_url": "https://logos.composio.dev/api/lyzr",
  "categories": [
    "ai & machine learning"
  ],
  "is_composio_managed": false,
  "updated_at": "2026-10-04T15:01:12.151Z"
}
```

![Lyzr logo](https://logos.composio.dev/api/lyzr)

## Description

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with Lyzr MCP or direct API to build agents, run evaluations, manage knowledge bases, and orchestrate workflows through natural language.

## Summary

Lyzr is an AI agent platform for building, running, evaluating, and managing agents.
It helps teams ship safer AI workflows with Studio services for memory, voice, simulations, and knowledge bases.

## Categories

- ai & machine learning

## Toolkit Details

- Tools: 22

## Images

- Logo: https://logos.composio.dev/api/lyzr

## Authentication

- **Api Key**
  - Type: `api_key`
  - Description: Api Key authentication for Lyzr.
  - Setup:
    - Configure Api Key credentials for Lyzr.
    - Use the credentials when creating an auth config in Composio.

## Suggested Prompts

- Create a Lyzr agent evaluation report
- Run responsible AI checks on agents
- Schedule Lyzr workflow for lead scoring

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `LYZR_ADD_MEMORY_MESSAGES` | Add Memory Messages | Store a batch of conversation messages in Lyzr Memory for an owner, session, and optional agent, with optional synchronous fact extraction. |
| `LYZR_CHAT_WITH_AGENT` | Chat With Agent | Send a message or message history to an active Agent Studio agent and return its synchronous inference response for a session. |
| `LYZR_CLEAR_MEMORY_SESSION` | Clear Memory Session | Permanently clear messages and memories for one explicit owner and session in Lyzr Memory. Cross-session deletion is always disabled. |
| `LYZR_CREATE_AGENT` | Create Agent | Create a single-task Agent Studio agent with an LLM provider, model, instructions, and optional tool configuration. |
| `LYZR_CREATE_AGENT_SCHEDULE` | Create Agent Schedule | Create a cron schedule that runs one Agent Studio agent with a message in a specified timezone. |
| `LYZR_DELETE_AGENT` | Delete Agent | Permanently delete one Agent Studio agent by ID. |
| `LYZR_DELETE_AGENT_SCHEDULE` | Delete Agent Schedule | Permanently delete one agent cron schedule and remove its associated scheduler job. |
| `LYZR_EVALUATE_TEXT_WITH_RAI_POLICY` | Evaluate Text With RAI Policy | Apply one owned Responsible AI policy to text and return processed text, block decisions, warnings, detections, and redactions. |
| `LYZR_GET_AGENT` | Get Agent | Return the current configuration and status of one Agent Studio agent by ID. |
| `LYZR_GET_KNOWLEDGE_BASE` | Get Knowledge Base | Return one Lyzr Knowledge Base configuration by its known RAG configuration ID. |
| `LYZR_GET_SIMULATION_OVERVIEW` | Get Simulation Overview | Return aggregate Agent Simulation counts and average evaluation pass rate for the connected workspace. |
| `LYZR_LIST_AGENTS` | List Agents | Return all Agent Studio agents owned by the connected API key, including IDs needed by lifecycle and inference tools. |
| `LYZR_LIST_AGENT_SCHEDULES` | List Agent Schedules | Return one page of agent cron schedules, optionally filtered by user, agent, or active state. |
| `LYZR_LIST_AGENT_SIMULATION_ISSUES` | List Agent Simulation Issues | Return recent performance, error, and Responsible AI issues across monitored agents, optionally filtered by resolution and severity. |
| `LYZR_LIST_RAI_POLICIES` | List RAI Policies | Return Responsible AI policies owned by the authenticated user, including policy IDs and enabled guardrail configuration. |
| `LYZR_LIST_SUPERFLOW_EXECUTIONS` | List SuperFlow Executions | Return one page of SuperFlow execution records, optionally filtered by workflow and execution status. |
| `LYZR_LIST_SUPERFLOW_WORKFLOWS` | List SuperFlow Workflows | Return all SuperFlow workflow definitions accessible to the connected API key, including workflow IDs and graph data. |
| `LYZR_LIST_VOICE_AGENTS` | List Voice Agents | Return saved Voice agents accessible to the connected organization, including IDs used to filter transcripts. |
| `LYZR_LIST_VOICE_TRANSCRIPTS` | List Voice Transcripts | Return one page of accessible Voice call transcripts, optionally filtered by agent, session, organization, or date range. |
| `LYZR_RETRIEVE_KNOWLEDGE` | Retrieve Knowledge | Retrieve relevant documents from a known Lyzr Knowledge Base using configurable basic, MMR, hypothetical-document, or time-aware retrieval. |
| `LYZR_SEARCH_MEMORIES` | Search Memories | Semantically search stored memories for one owner, within one session or across that owner's sessions, using Lyzr's hybrid vector and BM25 retrieval. |
| `LYZR_SET_AGENT_STATUS` | Set Agent Status | Activate or deactivate an Agent Studio agent. Deactivated agents reject inference until reactivated. |

## Supported Triggers

None listed.

## Installation and MCP Setup

### Path 1: SDK Installation

#### Path 1, Step 1: Install Composio

Install the Composio SDK, the OpenAI provider, and the OpenAI SDK
```python
pip install composio composio_openai openai
```

```typescript
npm install @composio/core @composio/openai openai
```

#### Path 1, Step 2: Create a Composio session

Initialize Composio with the OpenAI Responses provider and create a session scoped to Lyzr
```python
import json
from openai import OpenAI
from composio import Composio
from composio_openai import OpenAIResponsesProvider

composio = Composio(provider=OpenAIResponsesProvider())
client = OpenAI()

session = composio.create(user_id="your-user-id", toolkits=["lyzr"])
tools = session.tools()
```

```typescript
import OpenAI from "openai";
import { Composio } from "@composio/core";
import { OpenAIResponsesProvider } from "@composio/openai";

const composio = new Composio({ provider: new OpenAIResponsesProvider() });
const client = new OpenAI();

const session = await composio.create("your-user-id", { toolkits: ["lyzr"] });
const tools = await session.tools();
```

#### Path 1, Step 3: Run Lyzr tools with your agent

Send a request, execute the Lyzr tool calls through the session, and print the final answer
```python
response = client.responses.create(
    model="gpt-5.6-sol",
    tools=tools,
    input=[{"role": "user", "content": "List my Lyzr Studio agents and summarize their latest evaluation status"}],
)

while True:
    tool_calls = [o for o in response.output if o.type == "function_call"]
    if not tool_calls:
        break
    results = composio.provider.handle_tool_calls(response=response, session=session)
    response = client.responses.create(
        model="gpt-5.6-sol",
        tools=tools,
        previous_response_id=response.id,
        input=[
            {"type": "function_call_output", "call_id": call.call_id, "output": json.dumps(results[i])}
            for i, call in enumerate(tool_calls)
        ],
    )

print(response.output_text)
```

```typescript
let response = await client.responses.create({
  model: "gpt-5.6-sol",
  tools,
  input: [{ role: "user", content: "List my Lyzr Studio agents and summarize their latest evaluation status" }],
});

while (response.output.some((o) => o.type === "function_call")) {
  const outputs = await composio.provider.handleToolCalls(session, response.output);
  response = await client.responses.create({
    model: "gpt-5.6-sol",
    tools,
    previous_response_id: response.id,
    input: outputs,
  });
}

console.log(response.output_text);
```

### Path 2: MCP Server Setup

#### Path 2, Step 1: Install Composio

Install the Composio SDK and your agent framework
```python
pip install composio claude-agent-sdk
```

```typescript
npm install @composio/core ai @ai-sdk/mcp @ai-sdk/openai
```

#### Path 2, Step 2: Create a session with MCP enabled

Create a session scoped to Lyzr and read its MCP URL and headers
```python
from composio import Composio

composio = Composio()
session = composio.create(user_id="your-user-id", toolkits=["lyzr"], mcp=True)
```

```typescript
import { Composio } from "@composio/core";

const composio = new Composio();
const { mcp } = await composio.create("your-user-id", {
  toolkits: ["lyzr"],
  mcp: true,
});
```

#### Path 2, Step 3: Connect your agent to the MCP server

Pass the session's MCP URL and headers to your agent and run a Lyzr request
```python
import asyncio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions, AssistantMessage, TextBlock

options = ClaudeAgentOptions(
    mcp_servers={
        "composio": {
            "type": "http",
            "url": session.mcp.url,
            "headers": session.mcp.headers,
        }
    },
    system_prompt="You are a helpful assistant with access to Lyzr tools.",
    tools=[],
    allowed_tools=["mcp__composio__*"],
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query("List my Lyzr Studio agents and summarize their latest evaluation status")
        async for message in client.receive_response():
            if isinstance(message, AssistantMessage):
                for block in message.content:
                    if isinstance(block, TextBlock):
                        print(block.text)

asyncio.run(main())
```

```typescript
import { createMCPClient } from "@ai-sdk/mcp";
import { openai } from "@ai-sdk/openai";
import { generateText, stepCountIs } from "ai";

const client = await createMCPClient({
  transport: { type: "http", url: mcp.url, headers: mcp.headers },
});

const { text } = await generateText({
  model: openai("gpt-5.6-sol"),
  tools: await client.tools(),
  prompt: "List my Lyzr Studio agents and summarize their latest evaluation status",
  stopWhen: stepCountIs(10),
});

console.log(text);
await client.close();
```

## Why Use Composio?

### 1. AI Native Lyzr Integration

- Supports both Lyzr MCP and direct API based integrations
- Structured, LLM-friendly schemas for reliable Lyzr agent, workflow, and knowledge base actions
- Rich coverage for building, running, evaluating, and managing your Lyzr Studio services

### 2. Managed Auth

- Secure API key handling without hard-coding Lyzr credentials in your agent code
- Central place to manage, scope, and revoke Lyzr access
- Per user and per environment credentials so dev, staging, and production stay clean

### 3. Agent Optimized Design

- Tools are tuned using real error and success rates to improve reliability over time
- Comprehensive execution logs so you always know what ran, when, and on whose behalf
- Clear tool inputs help agents work with Lyzr evaluations, simulations, memory, and workflows with fewer failed calls

### 4. Enterprise Grade Security

- Fine-grained RBAC so you control which agents and users can access Lyzr
- Scoped, least privilege access to Lyzr agents, workflows, and Studio resources
- Full audit trail of agent actions to support review, debugging, and compliance

## Use Lyzr with any AI Agent Framework

Choose a framework you want to connect Lyzr with:

None listed.

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## Frequently Asked Questions

### Do I need my own developer credentials to use Lyzr with Composio?

Yes, Lyzr requires you to configure your own API key credentials. Once set up, Composio handles secure credential storage and API request handling for you.

### Can I use multiple toolkits together?

Yes! Composio's Tool Router enables agents to use multiple toolkits. [Learn more](https://docs.composio.dev/tool-router/overview).

### Is Composio secure?

Composio is SOC 2 and ISO 27001 compliant with all data encrypted in transit and at rest. [Learn more](https://trust.composio.dev).

### What if the API changes?

Composio maintains and updates all toolkit integrations automatically, so your agents always work with the latest API versions.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)