# How to integrate Needle MCP with CrewAI

```json
{
  "title": "How to integrate Needle MCP with CrewAI",
  "toolkit": "Needle",
  "toolkit_slug": "needle",
  "framework": "CrewAI",
  "framework_slug": "crew-ai",
  "url": "https://composio.dev/toolkits/needle/framework/crew-ai",
  "markdown_url": "https://composio.dev/toolkits/needle/framework/crew-ai.md",
  "updated_at": "2026-05-12T10:19:54.008Z"
}
```

## Introduction

This guide walks you through connecting Needle to CrewAI using the Composio tool router. By the end, you'll have a working Needle agent that can list all document collections i have, show stats for your 'research' collection, find files in collection uploaded this week through natural language commands.
This guide will help you understand how to give your CrewAI agent real control over a Needle account through Composio's Needle MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Needle with

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

## TL;DR

Here's what you'll learn:
- Get a Composio API key and configure your Needle connection
- Set up CrewAI with an MCP enabled agent
- Create a Tool Router session or standalone MCP server for Needle
- Build a conversational loop where your agent can execute Needle operations

## What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.
Key features include:
- Agent Roles: Define specialized agents with specific goals and backstories
- Task Management: Create tasks with clear descriptions and expected outputs
- Crew Orchestration: Combine agents and tasks into collaborative workflows
- MCP Integration: Connect to external tools through Model Context Protocol

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

The Needle MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Needle account. It provides structured and secure access to your semantic search collections, so your agent can perform actions like creating and managing collections, uploading and deleting files, retrieving collection statistics, and listing available data sources on your behalf.
- Collection management and creation: Easily instruct your agent to create new semantic search collections tailored to your data needs.
- File listing and retrieval: Have your agent list and retrieve all files within a specific collection, making it simple to view and organize your indexed data.
- File deletion from collections: Direct your agent to remove unwanted or outdated files from any collection by specifying file IDs for cleanup and maintenance.
- Collection statistics and insights: Ask your agent to fetch real-time statistics on any collection, including document counts, index size, and timestamps to monitor your data health.
- Browse all available collections: Let your agent page through and present all your collections, so you can quickly access, search, or manage your data resources.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `NEEDLE_ADD_FILES_TO_COLLECTION` | Add files to a collection | Tool to add files to a collection by providing file URLs. Use when you need to add one or more files to an existing collection. URLs can be public or private (generated via the Files API). |
| `NEEDLE_ADD_FILES_TO_LOCAL_CONNECTOR` | Add Files to Local Connector | Tool to add files to a local connector by providing file metadata. Use when you need to add external files to a connector using their URLs. |
| `NEEDLE_CREATE_COLLECTION` | Create Collection | Tool to create a new collection. Use after confirming the collection name. |
| `NEEDLE_CREATE_LOCAL_CONNECTOR` | Create Local Connector | Tool to create a local connector that monitors specified folders on a device. Use when setting up file indexing from a local machine into Needle collections. |
| `NEEDLE_DELETE_FILES_FROM_COLLECTION` | Delete files from a collection | Tool to delete files from a specific collection by providing file IDs. Use after confirming valid file IDs to remove from the collection. |
| `NEEDLE_DELETE_FILES_FROM_LOCAL_CONNECTOR` | Delete files from local connector | Tool to delete files from a local connector by filename or file IDs. Use when you need to remove files from a connector's local storage. |
| `NEEDLE_GET_COLLECTION` | Get Collection | Tool to retrieve details for a specific collection by its ID. Use when you need to get collection metadata including name, creation date, and search query count. |
| `NEEDLE_GET_COLLECTION_STATS` | Get collection stats | Tool to retrieve statistics for a specific collection by its ID. Use when you need document count, index size, and timestamps after confirming the collection exists. Zero document count is a valid response for empty collections, not an error. |
| `NEEDLE_GET_FILE_DOWNLOAD_URL` | Get File Download URL | Tool to get a short-lived signed private download URL for a Needle file. Use when you need to retrieve file content but the public storage URL requires authentication. The returned URL should be used immediately as it expires quickly. |
| `NEEDLE_GET_FILE_UPLOAD_URL` | Get File Upload URL | Tool to get signed URLs for uploading local files to Needle. Use when you need to upload files to a collection. The upload URLs are valid for a short time, so upload files immediately after receiving the URLs. Multiple content types can be specified to generate multiple upload URLs in a single request. |
| `NEEDLE_GET_LOCAL_CONNECTOR` | Get local connector | Tool to retrieve details of a local connector by its ID. Use when you need information about a specific local connector's configuration, device details, and associated folders. |
| `NEEDLE_LIST_COLLECTION_FILES` | List Collection Files | Tool to list all files within a specific collection by its ID. Returns file metadata (including file URLs) only — not document text content; fetch file URLs separately to access content. Use when you have a collection ID and need to retrieve its files. Supports pagination. |
| `NEEDLE_LIST_COLLECTIONS` | List Collections | Tool to list collections. Use after authenticating with your API key to page through collections. Similar collection names can exist; always verify the correct `collection_id` from results before performing subsequent operations. |
| `NEEDLE_LIST_CONNECTORS` | List Connectors | Tool to list connectors. Use to retrieve all configured connectors in your account. |
| `NEEDLE_LIST_LOCAL_CONNECTORS` | List Local Connectors | Tool to list local connectors. Use to retrieve all local connectors configured in your Needle account. |
| `NEEDLE_SEARCH_COLLECTION` | Search Collection | Tool to perform semantic search within a specific Needle collection and return ranked results with source references. Use when you need to retrieve relevant content from a known collection using natural language queries. |

## Supported Triggers

None listed.

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

The Needle MCP server is an implementation of the Model Context Protocol that connects your AI agent to Needle. It provides structured and secure access so your agent can perform Needle 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 starting, make sure you have:
- Python 3.9 or higher
- A Composio account and API key
- A Needle connection authorized in Composio
- An OpenAI API key for the CrewAI LLM
- Basic familiarity with Python

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

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider.
- Keep the API key safe.
Composio API Key
- Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

**What's happening:**
- composio connects your agent to Needle via MCP
- crewai provides Agent, Task, Crew, and LLM primitives
- crewai-tools[mcp] includes MCP helpers
- python-dotenv loads environment variables from .env
```bash
pip install composio crewai crewai-tools[mcp] python-dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates with Composio
- USER_ID scopes the session to your account
- OPENAI_API_KEY lets CrewAI use your chosen OpenAI model
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import dependencies

**What's happening:**
- CrewAI classes define agents and tasks, and run the workflow
- MCPServerHTTP connects the agent to an MCP endpoint
- Composio will give you a short lived Needle MCP URL
```python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

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

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")
```

### 5. Create a Composio Tool Router session for Needle

**What's happening:**
- You create a Needle only session through Composio
- Composio returns an MCP HTTP URL that exposes Needle tools
```python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["needle"])

url = session.mcp.url
```

### 6. Initialize the MCP Server

**What's Happening:**
- Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
- MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
- Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
- Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
- Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.
```python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
```

### 7. Create a CLI Chatloop and define the Crew

**What's Happening:**
- Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
- Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
- Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
- Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
- Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
- Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.
```python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
```

## Complete Code

```python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

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

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_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.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["needle"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")
```

## Conclusion

You now have a CrewAI agent connected to Needle through Composio's Tool Router. The agent can perform Needle operations through natural language commands.
Next steps:
- Add role-specific instructions to customize agent behavior
- Plug in more toolkits for multi-app workflows
- Chain tasks for complex multi-step operations

## How to build Needle MCP Agent with another framework

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

## Related Toolkits

- [Composio](https://composio.dev/toolkits/composio) - Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed.
- [Composio search](https://composio.dev/toolkits/composio_search) - Composio search is a unified web search toolkit spanning travel, e-commerce, news, financial markets, images, and more. It lets you and your apps tap into up-to-date web data from a single, easy-to-integrate service.
- [Perplexityai](https://composio.dev/toolkits/perplexityai) - Perplexityai delivers natural, conversational AI models for generating human-like text. Instantly get context-aware, high-quality responses for chat, search, or complex workflows.
- [Browser tool](https://composio.dev/toolkits/browser_tool) - Browser tool is a virtual browser integration that lets AI agents interact with the web programmatically. It enables automated browsing, scraping, and action-taking from any AI workflow.
- [Ai ml api](https://composio.dev/toolkits/ai_ml_api) - Ai ml api is a suite of AI/ML models for natural language and image tasks. It provides fast, scalable access to advanced AI capabilities for your apps and workflows.
- [Aivoov](https://composio.dev/toolkits/aivoov) - Aivoov is an AI-powered text-to-speech platform offering 1,000+ voices in over 150 languages. Instantly turn written content into natural, human-like audio for any application.
- [All images ai](https://composio.dev/toolkits/all_images_ai) - All-Images.ai is an AI-powered image generation and management platform. It helps you create, search, and organize images effortlessly with advanced AI capabilities.
- [Anthropic administrator](https://composio.dev/toolkits/anthropic_administrator) - Anthropic administrator is an API for managing Anthropic organizational resources like members, workspaces, and API keys. It helps you automate admin tasks and streamline resource management across your Anthropic organization.
- [Api labz](https://composio.dev/toolkits/api_labz) - Api labz is a platform offering a suite of AI-driven APIs and workflow tools. It helps developers automate tasks and build smarter, more efficient applications.
- [Apipie ai](https://composio.dev/toolkits/apipie_ai) - Apipie ai is an AI model aggregator offering a single API for accessing top AI models from multiple providers. It helps developers build cost-efficient, latency-optimized AI solutions without juggling multiple integrations.
- [Astica ai](https://composio.dev/toolkits/astica_ai) - Astica ai provides APIs for computer vision, NLP, and voice synthesis. Integrate advanced AI features into your app with a single API key.
- [Bigml](https://composio.dev/toolkits/bigml) - BigML is a machine learning platform that lets you build, train, and deploy predictive models from your data. Its intuitive interface and robust API make machine learning accessible and efficient.
- [Botbaba](https://composio.dev/toolkits/botbaba) - Botbaba is a platform for building, managing, and deploying conversational AI chatbots across messaging channels. It streamlines chatbot automation, making it easier to integrate AI into customer interactions.
- [Botpress](https://composio.dev/toolkits/botpress) - Botpress is an open-source platform for building, deploying, and managing chatbots. It helps teams automate conversations and deliver rich, interactive messaging experiences.
- [Chatbotkit](https://composio.dev/toolkits/chatbotkit) - Chatbotkit is a platform for building and managing AI-powered chatbots using robust APIs and SDKs. It lets you easily add conversational AI to your apps for better user engagement.
- [Cody](https://composio.dev/toolkits/cody) - Cody is an AI assistant built for businesses, trained on your company's knowledge and data. It delivers instant answers and insights, tailored for your team.
- [Context7 MCP](https://composio.dev/toolkits/context7_mcp) - Context7 MCP delivers live, version-specific code docs and examples right from the source. It helps developers and AI agents instantly retrieve authoritative programming info—no more out-of-date docs.
- [Customgpt](https://composio.dev/toolkits/customgpt) - CustomGPT.ai lets you build and deploy chatbots tailored to your own data and business needs. Get precise and context-aware AI conversations without writing code.
- [Datarobot](https://composio.dev/toolkits/datarobot) - Datarobot is a machine learning platform that automates model development, deployment, and monitoring. It empowers organizations to quickly gain predictive insights from large datasets.
- [Deepgram](https://composio.dev/toolkits/deepgram) - Deepgram is an AI-powered speech recognition platform for accurate audio transcription and understanding. It enables fast, scalable speech-to-text with advanced audio intelligence features.

## Frequently Asked Questions

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

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

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

Yes, you can. CrewAI 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 Needle tools.

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

Yes, absolutely. You can configure which Needle 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 Needle data and credentials are handled as safely as possible.

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