How to integrate Coda MCP with CrewAI

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Introduction

This guide walks you through connecting Coda to CrewAI using the Composio tool router. By the end, you'll have a working Coda agent that can duplicate my project tracker document, add a new permission for this doc, export the content of the roadmap page, create a new page in q2 planning doc through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Coda account through Composio's Coda MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

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

The Coda MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Coda account. It provides structured and secure access to your workspaces and docs, so your agent can automate Coda document creation, manage permissions, export content, and streamline your team’s productivity tools—all on your behalf.

  • Automated document and page creation: Instruct your agent to create new Coda documents or pages, duplicate existing docs, and organize content structure with just a prompt.
  • Flexible permission and sharing management: Have your agent add or modify user, workspace, or global permissions, so you’re always in control of who can view or edit your docs.
  • Seamless content export and status tracking: Let your agent initiate exports of Coda pages and check the progress, making it easy to share or archive important information.
  • Custom domain and publishing management: Direct your agent to add custom domains to published docs or manage categories and makers for Coda packs, keeping your workspace organized and discoverable.
  • Pack release and workspace enhancements: Ask your agent to create new pack releases or manage integrations, helping teams extend Coda’s power without repetitive manual steps.

Supported Tools & Triggers

Tools
Triggers
Add a category for packAdd a publishing category for a given pack.
Add a maker for packSet a maker for a given pack.
Add a permission for packCreate or modify user, workspace, or global permissions for a given pack.
Add custom domainAdd a custom domain to a published doc.
Add permissionAdds a new permission to the doc.
Begin content exportInitiate an export of content for the given page.
Content export statusCheck the status of a page content export
Copy DocumentCreates a copy of an existing coda document.
Create a new pack releaseCreates a new pack release based on an existing pack version.
Create a pageCreate a new page in a doc.
Create docCreates a new coda doc, optionally copying an existing doc.
Create packCreates a new pack, essentially registering a new pack id.
Delete a category for packDelete a publishing category for a given pack.
Delete a maker for packDelete a maker for a given pack, who will not be displayed in the corresponding packs page.
Delete a pageDeletes the specified page.
Delete a permission for packDelete user, workspace, or global permissions for a given pack.
Delete docDeletes a doc.
Delete multiple rowsDeletes the specified rows from the table or view.
Delete packDelete a given pack.
Delete permissionDeletes an existing permission.
Delete rowDeletes the specified row from the table or view.
Deletes a custom domainDeletes a custom domain from a published doc.
Fetch grouped logs by pack org root ingestion idRetrieve the grouped logs of a pack for debugging purpose.
Fetch ingestion executions for packRetrieve the ingestion execution ids of a root ingestion for debugging purpose.
Get acl settingsReturns settings associated with acls for this coda doc.
Get a columnReturns details about a column in a table.
Get a controlReturns info on a control.
Get a formulaReturns info on a formula.
Get analytics last updated dayReturns days based on pacific standard time when analytics were last updated.
Get a pageReturns details about a page.
Get a rowReturns details about a row in a table.
Get a single packReturns a single pack.
Get a tableReturns details about a specific table or view.
Get detailed listing information for a packGet detailed listing information for a pack.
Get doc analytics summaryReturns summarized analytics data for available docs.
Get doc categoriesGets all available doc categories.
Get info about a docReturns metadata for the specified doc.
Get mutation statusGet the status for an asynchronous mutation to know whether or not it has been completed.
Get pack analytics summaryReturns summarized analytics data for packs the user can edit.
Gets custom doc domains providersGets the provider (ie.
Get sharing metadataReturns metadata associated with sharing for this coda doc.
Gets the json schema for pack configurationReturns a json schema applicable for customizing the pack using pack configurations.
Get the difference between two pack versionsGets information about the difference between the specified previous version and next version of a pack.
Get the next valid version for a packGet the next valid version based on the proposed metadata.
Get the source code for a pack versionGet temporary links used to download the source code for the given packid and version
Get user infoReturns basic info about the current user.
List available docsReturns a list of coda docs accessible by the user, and which they have opened at least once.
List categories for packList publishing categories for a given pack.
List columnsReturns a list of columns in a table.
List controlsReturns a list of controls in a coda doc.
List custom doc domainsList all custom domains for a published doc.
List doc analyticsReturns analytics data for available docs per day.
List featured docs for a packReturns a list of featured doc ids for a pack.
List formulasReturns a list of named formulas in a coda doc.
List makers for packList makers for a given pack.
List pack analyticsReturns analytics data for packs the user can edit.
List pack formula analyticsReturns analytics data for pack formulas.
List packsGet the list of accessible packs.
List page analyticsReturns analytics data for a given doc within the day.
List pagesReturns a list of pages in a coda doc.
List permissionsReturns a list of permissions for this coda doc.
List permissions for a packGet user, workspace, and/or global permissions for a given pack.
List table rowsRetrieves rows from a specific table within a coda document.
List tablesReturns a list of tables in a coda doc.
List the pack listings accessible to a userGet listings of public packs and packs created by you.
List the releases for a packGet the list of releases of a pack.
List the versions for a packGet the list of versions of a pack.
List workspace rolesReturns a list of the counts of users over time by role for the workspace.
List workspace usersReturns a list of members in the given workspace.
Pack asset upload completeNote the completion of the upload of a pack asset.
Pack source code upload completeNote the completion of the upload of a pack source code.
Pack version upload completeNote the completion of the upload of a pack version bundle in order to create that pack version.
Patch the system connection credentials of the packPatch the system connection credentials of the pack.
Publish docUpdate publish settings for a doc.
Push a buttonPushes a button on a row in a table.
Register pack versionRegisters a new pack version.
Resolve browser linkGiven a browser link to a coda object, attempts to find it and return metadata that can be used to get more info on it.
Retrieve the grouped logs of a packRetrieve the grouped logs of a pack for debugging purpose.
Retrieve the information for a specific logRetrieve the ingestion execution ids of a root ingestion for debugging purpose.
Retrieve the logs of a ingestionRetrieve the logs of a ingestion for debugging purpose.
Retrieve the logs of a packRetrieve the logs of a pack for debugging purpose.
Retrieve the oauth configuration of the packRetrieve the oauth configuration of the pack for display purpose.
Retrieve the system connection metadata of the packRetrieve the system connection metadata of the pack.
Search Coda DocumentsThis tool allows users to search for coda documents based on a query term.
Search principalsSearches for user and group principals matching the query that this doc can be shared with.
Search Table RowsAction to search for rows in a coda table based on specific criteria.
Set the oauth configurations of the packSet the oauth configurations of the pack, including client id and secret.
Set the system connection credentials of the packSet the system connection credentials of the pack.
Trigger automationTriggers webhook-invoked automation
Unpublish docUnpublishes a doc.
Update acl settingsUpdate settings associated with acls for this coda doc.
Update an existing pack releaseUpdate details of a pack release.
Update a pageUpdate properties for a page.
Update docUpdates metadata for a doc.
Update featured docs for a packCreate or replace the featured docs for a pack.
Update packUpdate an existing pack for non-versioned fields.
Updates a custom domainUpdates properties of a document's custom domain.
Updates user roleUpdates the workspace user role of a user that matches the parameters.
Upload a pack assetRequest a signed s3 url to upload your pack asset.
Upload pack source codeRequest a signed s3 url to upload your pack source code.
Insert/Update Rows in Coda TableThis tool allows you to insert new rows into a coda table or update existing ones based on specified key columns.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Coda connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

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

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

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

Import dependencies

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional import if you plan to adapt tools
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()
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 Coda MCP URL

Create a Composio Tool Router session for Coda

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["coda"],
)
url = session.mcp.url
What's happening:
  • You create a Coda only session through Composio
  • Composio returns an MCP HTTP URL that exposes Coda tools

Configure the LLM

python
llm = LLM(
    model="gpt-5-mini",
    api_key=os.getenv("OPENAI_API_KEY"),
)
What's happening:
  • CrewAI will call this LLM for planning and responses
  • You can swap in a different model if needed

Attach the MCP server and create the agent

python
toolkit_agent = Agent(
    role="Coda Assistant",
    goal="Help users interact with Coda through natural language commands",
    backstory=(
        "You are an expert assistant with access to Coda tools. "
        "You can perform various Coda operations on behalf of the user."
    ),
    mcps=[
        MCPServerHTTP(
            url=url,
            streamable=True,
            cache_tools_list=True,
            headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
        ),
    ],
    llm=llm,
    verbose=True,
    max_iter=10,
)
What's happening:
  • MCPServerHTTP connects the agent to the Coda MCP endpoint
  • cache_tools_list saves a tools catalog for faster subsequent runs
  • verbose helps you see what the agent is doing

Add a REPL loop with Task and Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to perform Coda operations.\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"Based on the conversation history:\n{conversation_context}\n\n"
            f"Current user request: {user_input}\n\n"
            f"Please help the user with their Coda related request."
        ),
        expected_output="A helpful response addressing the user's request",
        agent=toolkit_agent,
    )

    crew = Crew(
        agents=[toolkit_agent],
        tasks=[task],
        verbose=False,
    )

    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's happening:
  • You build a simple chat loop and keep a running context
  • Each user turn becomes a Task handled by the same agent
  • Crew executes the task and returns a response

Run the application

python
if __name__ == "__main__":
    main()
What's happening:
  • Standard Python entry point so you can run python crewai_coda_agent.py

Complete Code

Here's the complete code to get you started with Coda and CrewAI:

python
# file: crewai_coda_agent.py
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()

def main():
    # Initialize Composio and create a Coda session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["coda"],
    )
    url = session.mcp.url

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

    # Create Coda assistant agent
    toolkit_agent = Agent(
        role="Coda Assistant",
        goal="Help users interact with Coda through natural language commands",
        backstory=(
            "You are an expert assistant with access to Coda tools. "
            "You can perform various Coda operations on behalf of the user."
        ),
        mcps=[
            MCPServerHTTP(
                url=url,
                streamable=True,
                cache_tools_list=True,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
            ),
        ],
        llm=llm,
        verbose=True,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Try asking the agent to perform Coda operations.\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"Based on the conversation history:\n{conversation_context}\n\n"
                f"Current user request: {user_input}\n\n"
                f"Please help the user with their Coda related request."
            ),
            expected_output="A helpful response addressing the user's request",
            agent=toolkit_agent,
        )

        crew = Crew(
            agents=[toolkit_agent],
            tasks=[task],
            verbose=False,
        )

        result = crew.kickoff()
        response = str(result)

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

if __name__ == "__main__":
    main()

Conclusion

You now have a CrewAI agent connected to Coda through Composio's Tool Router. The agent can perform Coda 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 Coda MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Coda MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Coda MCP with Claude Agent SDK

Google ADK

Google ADK

Use Coda MCP with Google ADK

LangChain

LangChain

Use Coda MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Coda MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Coda MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Coda MCP with LlamaIndex

FAQ

What are the differences in Tool Router MCP and Coda MCP?

With a standalone Coda MCP server, the agents and LLMs can only access a fixed set of Coda tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Coda 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 Coda tools.

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

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

Used by agents from

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