# How to integrate Enigma MCP with LlamaIndex

```json
{
  "title": "How to integrate Enigma MCP with LlamaIndex",
  "toolkit": "Enigma",
  "toolkit_slug": "enigma",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/enigma/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/enigma/framework/llama-index.md",
  "updated_at": "2026-05-12T10:10:26.867Z"
}
```

## Introduction

This guide walks you through connecting Enigma to LlamaIndex using the Composio tool router. By the end, you'll have a working Enigma agent that can verify the legitimacy of acme corp in delaware, check if a business is on any u.s. sanctions list, get detailed kyb info for a california llc through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Enigma account through Composio's Enigma MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Enigma with

- [OpenAI Agents SDK](https://composio.dev/toolkits/enigma/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/enigma/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/enigma/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/enigma/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/enigma/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/enigma/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/enigma/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/enigma/framework/cli)
- [Google ADK](https://composio.dev/toolkits/enigma/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/enigma/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/enigma/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/enigma/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/enigma/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Set your OpenAI and Composio API keys
- Install LlamaIndex and Composio packages
- Create a Composio Tool Router session for Enigma
- Connect LlamaIndex to the Enigma MCP server
- Build a Enigma-powered agent using LlamaIndex
- Interact with Enigma through natural language

## What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.
Key features include:
- ReAct Agent: Reasoning and acting pattern for tool-using agents
- MCP Tools: Native support for Model Context Protocol
- Context Management: Maintain conversation context across interactions
- Async Support: Built for async/await patterns

## What is the Enigma MCP server, and what's possible with it?

The Enigma MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Enigma account. It provides structured and secure access to comprehensive U.S. business data, so your agent can perform actions like verifying company identities, screening for compliance, and assessing financial health automatically.
- Automated KYB business verification: Rapidly verify the legitimacy of U.S. businesses by checking official state records, brands, and legal entities through your agent.
- Sanctions and watchlist screening: Instantly screen businesses and transactions against up-to-date sanctions and watchlists for enhanced compliance and risk mitigation.
- Retrieve detailed business intelligence: Access comprehensive profiles on businesses, including best match results, affiliated brands, and entity structures.
- Compliance automation: Let your agent independently run verification checks and screenings to streamline onboarding, due diligence, and regulatory workflows.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `ENIGMA_CREATE_LIST` | Create List | Tool to create a new list to organize and group entities in Enigma. Use when you need to create a list for data generation or enrichment purposes. The list can be populated using search criteria (entityType and prompt) to find matching entities. |
| `ENIGMA_CREATE_SUGGESTION` | Create Suggestion | Tool to create a suggestion for data correction, enhancement, or analysis feedback in Enigma. Use when you need to submit feedback or suggest improvements to data in the Enigma platform. |
| `ENIGMA_DELETE_LIST` | Delete List | Tool to delete an existing list permanently from the system. Use when you need to remove a list by its ID. Returns confirmation with the ID of the deleted list. |
| `ENIGMA_GET_ACCOUNT` | Get Account Information | Tool to retrieve information about the current API account via GraphQL. Use when you need to check customer ID, billing details, pricing plan, credit availability, or auto-recharge settings. |
| `ENIGMA_GET_AGGREGATE_COUNTS` | Get Aggregate Counts | Tool to get aggregate counts of operating locations and their associated brands or legal entities. Use when you need summary counts rather than detailed entity information. Supports filtering by open operating locations. |
| `ENIGMA_GET_ATTRIBUTE_GROUPS` | Get Attribute Groups | Tool to retrieve attribute groups for Enigma entity types. Returns JSON metadata describing available attributes organized into logical groups (ID, Name, Address, etc.) with their corresponding GraphQL field paths. Use when you need to discover queryable fields for Brand, OperatingLocation, or LegalEntity entities. |
| `ENIGMA_GET_BACKGROUND_TASK` | Get Background Task Status | Tool to get the status and results of a background task by ID. Use when checking async operation progress or retrieving results from previously initiated long-running operations. |
| `ENIGMA_GET_BUSINESS` | Get Business by Enigma ID | Tool to retrieve detailed business information using an Enigma ID. Returns comprehensive business profile including addresses, names, websites, associated people, industries, and more. Use when you need complete business details for a specific Enigma ID obtained from a prior search or match operation. |
| `ENIGMA_GET_DECISION` | Get Screening Decision | Tool to retrieve a screening decision by its request ID. Use when you need to check the status, alert status, assignee, or timestamps of a previously created decision. Requires case management to be enabled for the account. |
| `ENIGMA_GET_GRAPH_QL_SCHEMA_EXTENDED` | Get Extended GraphQL Schema | Tool to retrieve extended schema information for Enigma's GraphQL API. Returns metadata about available types, fields, projections, and data asset metadata. Use when you need to explore the GraphQL schema structure or understand what data types and fields are available. |
| `ENIGMA_GET_LIST_MATERIALIZATION` | Get List Materialization | Tool to retrieve a specific list materialization by its unique ID. Returns detailed information about the materialized list including status, progress, and results location. Use when you need to check the status or retrieve results of a list materialization operation. |
| `ENIGMA_GET_SANCTIONED_ENTITY` | Get Sanctioned Entity Details | Tool to retrieve detailed information about a specific sanctioned entity by its ID. Returns full entity profile including names, aliases, DOB, nationality, addresses, documents, and program designations. Use this when you need complete information about a known sanctioned entity from screening results. |
| `ENIGMA_KYB_VERIFICATION` | KYB Business Verification | This tool performs a Know Your Business (KYB) check on a U.S. business by querying Enigma's dataset of legal entities based on official state records. It verifies business information and returns comprehensive details about the business, including best match, legal entities, brands, and watchlists. Supports U.S. businesses only. |
| `ENIGMA_LIST_DECISIONS` | List Screening Decisions | Tool to retrieve multiple screening decisions with pagination and filtering options. Use when you need to list, search, or review historical screening decisions by alert status, assignee, date range, tag, or decision status. |
| `ENIGMA_MATCH_BUSINESS` | Match Business Profile | Tool to match business records against Enigma's SMB data asset using fuzzy matching on business name and location. Use when you need to identify a business profile and obtain an Enigma ID for further data retrieval. |
| `ENIGMA_SCREENING_VERIFICATION` | Screen Against Sanctions and Watchlists | A tool to screen customers and transactions against sanctions and other watchlists. This endpoint allows for independent verification without requiring any external resource IDs. |
| `ENIGMA_SEARCH_GRAPH_QL` | Search Enigma Entities via GraphQL | Tool to search and retrieve entities from Enigma's comprehensive U.S. business database. Returns brands (customer-facing identities), operating locations (physical/virtual spaces), or legal entities (government registrations) based on search criteria. Search precision is approximately 94% for all entity types. Use when you need to find business information by name, address, phone, website, or TIN. |
| `ENIGMA_SEARCH_LISTS` | Search User-Created Lists | Tool to search and retrieve user-created lists via GraphQL. Returns paginated list connections with cursor-based pagination. Use when you need to query, filter, or browse entity lists. |
| `ENIGMA_VERIFY_BUSINESS_V2` | Verify Business Identity (KYB v2) | Tool to verify business identity using Enigma's KYB v2 endpoint. Performs comprehensive business verification including TIN verification, SSN verification, watchlist screening, and business bankruptcy checks. This is the current recommended version of the KYB API. Use when you need to verify a business's identity, check compliance, or assess business risk. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Enigma MCP server is an implementation of the Model Context Protocol that connects your AI agent to Enigma. It provides structured and secure access so your agent can perform Enigma operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before you begin, make sure you have:
- Python 3.8/Node 16 or higher installed
- A Composio account with the API key
- An OpenAI API key
- A Enigma account and project
- Basic familiarity with async Python/Typescript

### 1. Getting API Keys for OpenAI, Composio, and Enigma

No description provided.

### 2. Installing dependencies

No description provided.
```python
pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv
```

```typescript
npm install @composio/llamaindex @llamaindex/openai @llamaindex/tools @llamaindex/workflow dotenv
```

### 3. Set environment variables

Create a .env file in your project root:
These credentials will be used to:
- Authenticate with OpenAI's GPT-5 model
- Connect to Composio's Tool Router
- Identify your Composio user session for Enigma access
```bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id
```

### 4. Import modules

No description provided.
```python
import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()
```

```typescript
import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

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

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();
```

### 5. Load environment variables and initialize Composio

No description provided.
```python
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")
```

```typescript
const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!COMPOSIO_API_KEY) throw new Error("COMPOSIO_API_KEY is not set");
if (!COMPOSIO_USER_ID) throw new Error("COMPOSIO_USER_ID is not set");
```

### 6. Create a Tool Router session and build the agent function

What's happening here:
- We create a Composio client using your API key and configure it with the LlamaIndex provider
- We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, enigma)
- The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
- LlamaIndex will connect to this endpoint to dynamically discover and use the available Enigma tools.
- The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.
```python
async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["enigma"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Enigma actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Enigma actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)
```

```typescript
async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["enigma"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
        description : "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Enigma actions." ,
    llm,
    tools,
  });

  return agent;
}
```

### 7. Create an interactive chat loop

No description provided.
```python
async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")
```

```typescript
async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}
```

### 8. Define the main entry point

What's happening here:
- We're orchestrating the entire application flow
- The agent gets built with proper error handling
- Then we kick off the interactive chat loop so you can start talking to Enigma
```python
async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err) {
    console.error("Failed to start agent:", err);
    process.exit(1);
  }
}

main();
```

### 9. Run the agent

When prompted, authenticate and authorise your agent with Enigma, then start asking questions.
```bash
python llamaindex_agent.py
```

```typescript
npx ts-node llamaindex-agent.ts
```

## Complete Code

```python
import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["enigma"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Enigma actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Enigma actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";
import { LlamaindexProvider } from "@composio/llamaindex";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) {
    throw new Error("OPENAI_API_KEY is not set in the environment");
  }
if (!COMPOSIO_API_KEY) {
    throw new Error("COMPOSIO_API_KEY is not set in the environment");
  }
if (!COMPOSIO_USER_ID) {
    throw new Error("COMPOSIO_USER_ID is not set in the environment");
  }

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["enigma"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
    description:
      "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Enigma actions." ,
    llm,
    tools,
  });

  return agent;
}

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err: any) {
    console.error("Failed to start agent:", err?.message ?? err);
    process.exit(1);
  }
}

main();
```

## Conclusion

You've successfully connected Enigma to LlamaIndex through Composio's Tool Router MCP layer.
Key takeaways:
- Tool Router dynamically exposes Enigma tools through an MCP endpoint
- LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
- The agent becomes more capable without increasing prompt size
- Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

## How to build Enigma MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/enigma/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/enigma/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/enigma/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/enigma/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/enigma/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/enigma/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/enigma/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/enigma/framework/cli)
- [Google ADK](https://composio.dev/toolkits/enigma/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/enigma/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/enigma/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/enigma/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/enigma/framework/crew-ai)

## Related Toolkits

- [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. It's the go-to tool for calculations, reporting, and flexible data management.
- [21risk](https://composio.dev/toolkits/_21risk) - 21RISK is a web app built for easy checklist, audit, and compliance management. It streamlines risk processes so teams can focus on what matters.
- [Abstract](https://composio.dev/toolkits/abstract) - Abstract provides a suite of APIs for automating data validation and enrichment tasks. It helps developers streamline workflows and ensure data quality with minimal effort.
- [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time.
- [Agentql](https://composio.dev/toolkits/agentql) - Agentql is a toolkit that connects AI agents to the web using a specialized query language. It enables structured web interaction and data extraction for smarter automations.
- [Agenty](https://composio.dev/toolkits/agenty) - Agenty is a web scraping and automation platform for extracting data and automating browser tasks—no coding needed. It streamlines data collection, monitoring, and repetitive online actions.
- [Ambee](https://composio.dev/toolkits/ambee) - Ambee is an environmental data platform providing real-time, hyperlocal APIs for air quality, weather, and pollen. Get precise environmental insights to power smarter decisions in your apps and workflows.
- [Ambient weather](https://composio.dev/toolkits/ambient_weather) - Ambient Weather is a platform for personal weather stations with a robust API for accessing local, real-time, and historical weather data. Get detailed environmental insights directly from your own sensors for smarter apps and automations.
- [Anonyflow](https://composio.dev/toolkits/anonyflow) - Anonyflow is a service for encryption-based data anonymization and secure data sharing. It helps organizations meet GDPR, CCPA, and HIPAA data privacy compliance requirements.
- [Api ninjas](https://composio.dev/toolkits/api_ninjas) - Api ninjas offers 120+ public APIs spanning categories like weather, finance, sports, and more. Developers use it to supercharge apps with real-time data and actionable endpoints.
- [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots.
- [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. It lets you automate data extraction and workflow tasks at scale—no infrastructure headaches.
- [Autom](https://composio.dev/toolkits/autom) - Autom is a lightning-fast search engine results data platform for Google, Bing, and Brave. Developers use it to access fresh, low-latency SERP data on demand.
- [Beaconchain](https://composio.dev/toolkits/beaconchain) - Beaconchain is a real-time analytics platform for Ethereum 2.0's Beacon Chain. It provides detailed insights into validators, blocks, and overall network performance.
- [Big data cloud](https://composio.dev/toolkits/big_data_cloud) - BigDataCloud provides APIs for geolocation, reverse geocoding, and address validation. Instantly access reliable location intelligence to enhance your applications and workflows.
- [Bigpicture io](https://composio.dev/toolkits/bigpicture_io) - BigPicture.io offers APIs for accessing detailed company and profile data. Instantly enrich your applications with up-to-date insights on 20M+ businesses.
- [Bitquery](https://composio.dev/toolkits/bitquery) - Bitquery is a blockchain data platform offering indexed, real-time, and historical data from 40+ blockchains via GraphQL APIs. Get unified, reliable access to complex on-chain data for analytics, trading, and research.
- [Brightdata](https://composio.dev/toolkits/brightdata) - Brightdata is a leading web data platform offering advanced scraping, SERP APIs, and anti-bot tools. It lets you collect public web data at scale, bypassing blocks and friction.
- [Builtwith](https://composio.dev/toolkits/builtwith) - BuiltWith is a web technology profiler that uncovers the technologies powering any website. Gain actionable insights into analytics, hosting, and content management stacks for smarter research and lead generation.
- [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Enigma MCP?

With a standalone Enigma MCP server, the agents and LLMs can only access a fixed set of Enigma tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Enigma and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with LlamaIndex?

Yes, you can. LlamaIndex fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Enigma tools.

### Can I manage the permissions and scopes for Enigma while using Tool Router?

Yes, absolutely. You can configure which Enigma scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

### How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Enigma data and credentials are handled as safely as possible.

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