MCP Servers

Pipedream offers dedicated MCP (Model Context Protocol) servers for all of our 2,500+ integrated apps. These servers enable AI assistants like Claude to securely access and interact with thousands of APIs through a standardized communication protocol, performing real-world tasks by connecting to your accounts.

Pipedream’s MCP servers are powered by Pipedream Connect, including:

Access to 2,500+ apps and APIs through a consistent interface
Over 10,000 pre-built tools and actions
Fully-managed OAuth and credential storage
Secure account connections with revocable access

User credentials are encrypted at rest and all requests are made through Pipedream’s servers, never directly exposing credentials to AI models. Read more about how we protect user credentials here.

Available MCP servers

Pipedream provides MCP servers for all our supported apps. Each app has its own dedicated MCP server with tools specific to that API. For example:

Slack MCP server: Send messages, manage channels, create reminders, and more
GitHub MCP server: Create issues, manage pull requests, search repositories
Google Sheets MCP server: Read and write data, format cells, create charts

Explore the full list of available MCP servers at mcp.pipedream.com.

Getting started

You can use Pipedream’s MCP servers in two ways:

As an end user: Connect your accounts through our hosted MCP servers at mcp.pipedream.com
As a developer: Host your own MCP servers for your application or organization

For end users

Set up MCP servers to use with any compatible MCP client, like Claude Desktop, Windsurf, Cursor, and VS Code.

Configure MCP servers and connect accounts

Navigate to mcp.pipedream.com and sign in or create an account (this is a separate account from pipdream.com)
Browse available MCP servers
Follow the configuration instructions on the server page to add it to your preferred MCP client
Connect your account (you can do this in the UI or the AI will prompt you when you first use a tool)

Start chatting

Ask the LLM or agent to perform tasks using your connected services. For example:

“Send a message to my team in Slack”
“Create a new issue in GitHub”
“Add data to my Google Sheet”

The AI will refer to the configured tools available in its MCP servers to complete the task.

Get things done

With MCP-enabled AI, you can:

Send messages and manage communication
Create and update documents
Query and analyze data
Automate workflows across your favorite tools

All using your own connected accounts with full control and security.

For developers

Deploy Pipedream’s MCP servers to your application or agent and make authenticated request on behalf of your customers. Refer to our reference implementation here.

Prerequisites

To run your own MCP server, you’ll need:

A Pipedream account
A Pipedream project. Accounts connected via MCP will be stored here.
Pipedream OAuth credentials

Set up environment variables

Set the following environment variables:

PIPEDREAM_CLIENT_ID=your_client_id
PIPEDREAM_CLIENT_SECRET=your_client_secret
PIPEDREAM_PROJECT_ID=your_project_id
PIPEDREAM_PROJECT_ENVIRONMENT=development

Run the MCP server

Pipedream’s MCP servers can run in two modes:

Stdio (for local testing)

npx @pipedream/mcp stdio --app slack --external-user-id user123

SSE (for hosting)

npx @pipedream/mcp sse

This exposes routes at:

GET /:external_user_id/:app - App-specific SSE connection endpoint
POST /:external_user_id/:app/messages - App-specific message handler

Where:

:external_user_id is your user’s unique identifier in your system
:app is the app slug (e.g., “slack”, “github”)

Customize for your needs

You can host and customize the MCP server for your specific requirements:

# Clone the repo
git clone https://github.com/PipedreamHQ/pipedream
cd pipedream/modelcontextprotocol
 
# Install dependencies
npm install
 
# Build
npm run build
 
# Run the SSE server
npm run start:sse:prod

See the MCP server README for detailed instructions on customization options.

Security

MCP servers follow strict security best practices:

Credential isolation: Each user’s credentials are stored securely and isolated from other users
No credential exposure: Credentials are never exposed to AI models or your client-side code
Request authentication: All requests to the MCP server are authenticated
Revocable access: Users can revoke access to their connected accounts at any time

For more information on security, see our security documentation.

Use cases

Pipedream’s MCP servers enable AI assistants to perform a wide range of tasks:

Productivity automation: Schedule meetings, send emails, create documents
Data analysis: Query databases, analyze spreadsheets, generate reports
Content creation: Post social media updates, create marketing materials
Customer support: Respond to inquiries, create tickets, update CRM records
Developer workflows: Create issues, review code, deploy applications

Supported tools

Each MCP server provides tools specific to that app. Tools are automatically created based on Pipedream’s registry of pre-built actions.
You can find the supported tools for a given app on its MCP server page or search for specific actions here: pipedream.com/expore.

Known gaps and limitations

Pipedream’s MCP server doesn’t yet support configuring dynamic props, which means LLMs may get confused when trying to configure props that require inputs from previous props
As an end user, you need to manually add distinct MCP servers for every app you want to interact with, instead of using a single MCP server that contains tools for many APIs

Pricing

Anyone can use Pipedream’s hosted MCP servers for their own use for free
To deploy Pipedream’s MCP servers to your own app or agent, you can get started for free in development mode
Visit the pricing page when you’re ready to ship to production

Additional resources

Pre-built tools API proxy