The Model Context Protocol (MCP) is an open standard that enables AI agents and automations to connect with external tools and data sources. Taskade's hosted MCP v2 connectors provide zero-setup, fully managed integration — giving your agents superpowers to interact with virtually any tool or service.
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The Three Pillars of Workspace DNA — MCP connectors enhance all three pillars: Memory (Projects & Databases), Intelligence (AI Agents), and Execution (Automations). They are the universal fabric that connects your workspace to the outside world.
What is MCP?
The Model Context Protocol (MCP) is an open, standardized protocol that provides a consistent way for AI models to discover and interact with external tools, APIs, and data sources. Think of it as a "USB-C for AI" — one universal connector that works with everything.
Instead of building custom integrations for each service, MCP provides a single protocol that any tool can implement. This means:
Universal connectivity — One protocol connects to any MCP-compatible service
Standardized tool discovery — AI agents automatically discover what tools are available and how to use them
Vendor-agnostic — Works across AI providers and tool ecosystems
Growing ecosystem — Hundreds of MCP servers available for popular services
How MCP Works in Taskade
Taskade implements MCP at two levels:
1. Hosted MCP v2 (Recommended)
Taskade manages everything for you. Hosted connectors run on Taskade's infrastructure with:
Zero setup — No server to deploy or maintain
Automatic authentication — OAuth flows handled by Taskade
High availability — Managed infrastructure with built-in retry logic
Stateless mode — Lightweight connectors for simple integrations (v6.117.0+)
2. Custom MCP Servers (BYO)
Connect your own MCP-compatible servers for proprietary tools or custom APIs:
Full control — Host on your own infrastructure
Custom tools — Expose any API or internal service as an MCP tool
On-premises data — Keep sensitive data within your network
Hosted MCP v2 Connectors
Taskade's Integrations Directory provides 100+ ready-to-use connectors. Browse them at taskade.com/integrations.
Native Integration Pieces (31)
These are deeply integrated with Taskade's automation engine and provide the richest experience:
Category | Integrations |
Communication | Slack (12 capabilities), Discord (6), Telegram Bot (11), Microsoft Teams (3), WhatsApp Business (3), Twilio (1) |
Gmail (4), MailChimp (1) | |
Google Workspace | Google Sheets (8), Google Drive (18), Google Calendar (4), Google Docs (4), Google Forms (1) |
CRM & Sales | HubSpot (5), Apollo (1) |
E-Commerce | Shopify (13), Stripe (20) |
Social Media | LinkedIn (2), Twitter/X (2), Facebook Pages (2), Reddit (2), YouTube (2) |
Developer | GitHub (11), HTTP Request (1) |
Forms & CMS | Typeform (1), Webflow (1), WordPress (1) |
Scheduling | Calendly (3), Schedule (1) |
Content | RSS (2), Zoom (3) |
MCP-Extended Connectors
Beyond the 31 native pieces, MCP v2 enables connection to any service that supports the protocol. The ecosystem is rapidly growing with servers for:
Database systems (PostgreSQL, MongoDB, Supabase)
Cloud platforms (AWS, Azure, GCP)
Development tools (Jira, Linear, Notion)
Knowledge bases (Confluence, GitBook)
Payment platforms (Square, PayPal)
Analytics tools (Mixpanel, Amplitude)
And many more...
Connecting an MCP Server
Step 1: Open Integrations Settings
Navigate to your workspace Settings → Integrations or click the Integrations icon in the sidebar.
Step 2: Browse or Add Connectors
For hosted connectors:
Browse the Integrations Directory
Click the connector you want to add
Follow the OAuth or API key setup flow
The connector is now available for agents and automations
For custom MCP servers:
Click Add MCP Server
Enter your MCP server URL
Taskade will discover available tools automatically
Configure authentication if required
Step 3: Enable Tools
Once connected, MCP tools appear in:
Agent tool settings — Toggle which MCP tools each agent can use
Automation builder — MCP actions appear alongside native actions
Using MCP with AI Agents
MCP connectors give your Custom AI Agents the ability to interact with external services during conversations.
How Agents Use MCP Tools
Tool discovery — The agent sees all available MCP tools with their descriptions and parameters
Autonomous tool selection — During a conversation, the agent decides which tool to use based on the user's request
Tool execution — The agent calls the MCP tool with appropriate parameters
Response integration — Tool results are incorporated into the agent's response
Example: Agent with Database MCP
Connect a PostgreSQL MCP server → Your agent can now:
Query database tables to answer questions
Insert or update records based on conversation context
Generate reports from live data
Monitor database health and alert on anomalies
Example: Agent with GitHub MCP
Connect the GitHub MCP connector → Your agent can:
Create and manage issues
Review pull requests
Search code repositories
Monitor release activity
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MCP tools are part of Taskade's Tools for AI Agents system. All tool usage follows your agent's permissions and knowledge training.
Using MCP with Automations
MCP connectors extend the Automation Engine with additional actions beyond the 31 native integration pieces.
How It Works
In the automation builder, add a new action step
Select an MCP tool from the connected servers
Configure the tool parameters (can use variables from previous steps)
The MCP action executes within your automation flow
Combining MCP with Native Actions
Create powerful workflows by chaining MCP actions with native Taskade actions:
Trigger: New form submission (native)
Action 1: Look up customer in CRM via MCP
Action 2: Enrich data with AI agent (native)
Action 3: Update external database via MCP
Action 4: Send Slack notification (native)
Building Custom MCP Servers
Developers can build their own MCP servers to expose custom APIs as Taskade tools. This is ideal for:
Internal tools — Connect proprietary APIs and internal services
Custom data sources — Expose databases, knowledge bases, or file systems
Specialized workflows — Build domain-specific tools for your agents
Getting Started
Choose a framework — Use an MCP SDK (available for TypeScript, Python, Java, and more)
Define your tools — Describe each tool with a name, description, and parameter schema
Implement handlers — Write the logic for each tool invocation
Deploy — Host your server on any infrastructure (cloud, edge, on-premises)
Connect to Taskade — Add your server URL in workspace settings
MCP Server Best Practices
Clear descriptions — Write human-readable descriptions so AI agents understand when and how to use each tool
Structured parameters — Define clear input/output schemas for reliable tool execution
Error handling — Return meaningful error messages that agents can interpret
Idempotency — Design tools that can safely be retried on failure
Security — Implement authentication and validate inputs
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For detailed API documentation and MCP server specifications, see the Taskade Developer API guide.
MCP FAQ
What AI models work with MCP?
MCP works with all AI models available in Taskade, including GPT-5.2, Claude Opus 4.5, Claude Sonnet 4.5, Gemini 3.1 Pro, and others. The model routes tool calls through Taskade's MCP connector layer.
Do MCP tools cost additional credits?
MCP tool calls use your plan's AI credits. Each tool invocation counts as part of the agent conversation or automation run that triggered it. There are no separate MCP fees.
Can I use MCP in Genesis apps?
Yes! Genesis apps can leverage MCP connectors through embedded agents and automations. This means your published apps can interact with external services, databases, and APIs.
What's the difference between hosted and self-hosted MCP?
Hosted (v2): Taskade manages the infrastructure. Zero setup, automatic scaling, built-in auth. Best for most users.
Self-hosted: You run the MCP server on your own infrastructure. Full control, access to private networks. Best for enterprise or custom tools.
Is MCP secure?
Yes. All MCP connections use encrypted HTTPS. Hosted connectors use Taskade's secure credential management. Self-hosted servers can implement their own authentication. All tool calls are logged in your automation history for full auditability.
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Ready to connect your tools? Create a workspace and start connecting MCP servers to your agents and automations.
Related Protocol: Agent-to-Agent (A2A)
In addition to MCP, the industry is developing the Agent-to-Agent Protocol (A2A) — Google's protocol for AI agents to discover, communicate, and delegate tasks across different platforms. While MCP connects agents to tools and data, A2A enables direct agent-to-agent communication for cross-platform collaboration.
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