Skip to main content
The Kadoa MCP server gives any compatible AI model or agent a standardized, secure way to work with Kadoa via the Model Context Protocol. It has tools for creating, running, and managing workflows, fetching and exporting extracted data, and configuring notifications, variables, and templates, all through natural language. Kadoa’s MCP server follows the authenticated remote MCP spec, so the server is centrally hosted and managed. For help getting started after setup, see some of our example prompts.

Setup

General

The server is centrally hosted and managed by Kadoa, using Streamable HTTP as its transport. There is nothing to install and no API key to manage. There are two ways to connect:
  • Personal connection (https://mcp.kadoa.com/mcp): You sign in with your own Kadoa account, and every tool call runs as you, under your role and active team. Best for individual use.
  • Service connector (https://service.mcp.kadoa.com/mcp): A workspace admin generates OAuth credentials once, and applications or organization members connect as a shared workspace service account, with no Kadoa login. Best for organization-wide rollouts and app contexts where nobody can sign in interactively. See MCP Service Connector →.
For a personal connection, add the server in your client: a browser opens so you can sign in with your Kadoa account and grant access. The connection then stays authorized; if a session expires, your client prompts you to sign in again.
With a personal connection, the MCP server acts as you: every tool runs under your Kadoa role and active team, and each action is recorded in the workflow’s history.
Instructions for specific clients follow below.

Claude

Team, Enterprise (Claude.ai) A Claude organization owner can roll Kadoa out to everyone at once: add a custom connector for https://mcp.kadoa.com/mcp under Admin settings → Connectors (members sign in with their own Kadoa accounts), or use the service connector so members connect without Kadoa accounts. Individual members can also add it themselves under Settings → Connectors → Add custom MCP with the same URL. Free, Pro (Claude.ai)
  1. Go to Settings → Connectors → Add custom MCP
  2. Enter the URL: https://mcp.kadoa.com/mcp
  3. Sign in with your Kadoa account via OAuth

Claude Code

Then run /mcp in a Claude Code session to go through the authentication flow.

Claude Desktop

Add the server to your Claude Desktop config file (create it if it doesn’t exist), then restart Claude Desktop:

ChatGPT

  1. Go to Settings → Connectors → Add MCP server
  2. Enter the URL: https://mcp.kadoa.com/mcp
  3. Choose OAuth authentication and sign in with your Kadoa account

Codex

Then run codex mcp login kadoa to go through the authentication flow. If this is your first remote MCP server in Codex, enable the rmcp client in ~/.codex/config.toml first:

Cursor

Gemini CLI

Others

Any MCP-compatible client can connect with the following settings:
  • URL: https://mcp.kadoa.com/mcp
  • Transport: Streamable HTTP
  • Auth: OAuth (sign in with your Kadoa account)

Permissions

The tools you can use depend on your team role. Viewers and Compliance Officers have read-only access: If a tool is not available for your role, you’ll receive an error message with instructions to contact your team admin.

Tools

The server exposes tools covering the full workflow lifecycle, notifications, variables, templates, and team management:
The status field returned by list_workflows and get_workflow shows the computed workflow state (Complete, Running, Failed, Paused, Scheduled, etc.) rather than just the raw lifecycle state. You can filter with list_workflows using the state parameter (ACTIVE, FAILED, PAUSED, PREVIEW).

Scheduling

The create_workflow tool accepts an interval parameter for recurring extractions (defaults to ONLY_ONCE). Use CUSTOM with cron expressions for fine-grained control. See Scheduling → for all available intervals and examples.

Fetching and exporting data

Two tools retrieve extracted data: use fetch_data for paginated reads (default 50 rows, max 500) with filters, sortBy, and order; use export_data for the full dataset. It returns a self-authenticating signed URL ideal for Claude for Excel (‘Get Data from Web’) or pandas/duckdb code execution.

Workflow history

get_workflow_history returns recent edit-audit entries for a workflow with field-level diffs (added, removed, and changed values) so you can see who modified what and when.

Common use cases

Once connected, you manage the full workflow lifecycle through natural conversation. Copy an example prompt into your client to explore what’s possible; see the tools above for the full surface:
Create a workflow that extracts product name, price, and rating from https://sandbox.kadoa.com/ecommerce, run it, and show me the first results.
Set up a workflow that scrapes competitor prices from https://sandbox.kadoa.com/ecommerce daily at 6:00, and email me when a run finishes or fails.
Show me all changes my real-time monitors detected this week and summarize what moved.
Export the full ‘Product Monitor’ dataset and analyze price trends by category.
Update the ‘Product Monitor’ schema to add a rating field, then pause the old ‘Legacy Scraper’ workflow.
Save ‘Product Monitor’ as a template called ‘Product Scraper’, then create a workflow from it for each of these five store URLs.
List my teams, switch to Acme Corp, and show me which workflows are failing there.

Troubleshooting

I don’t have access to Kadoa

  • Verify the MCP server is configured in the correct config file
  • Restart your MCP client after configuration changes
  • Re-authenticate via OAuth if prompted

Authentication failed

  • Your OAuth session may have expired, so re-authenticate when prompted by your MCP client
  • If switching teams, verify the team exists with team_list before using team_switch