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Model Context Protocol (MCP) enables CloudThinker to connect to custom tools and services. Use MCP to extend agent capabilities with your own connections.

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What is MCP?

MCP (Model Context Protocol) is an open protocol for connecting AI agents to external tools and data sources. It provides a standardized way to:
  • Expose tools that agents can call
  • Provide context and data to agents
  • Enable custom integrations with any service

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Setup

1

Prepare MCP server

Ensure your MCP server is running and accessible:
  • Supports Server-Sent Events (SSE) transport
  • Has a publicly accessible endpoint (or VPN access)
  • Returns proper MCP protocol responses
2

Create connection

Navigate to Connections → MCP and click Add MCP Connection.
3

Configure basic info

Enter connection details:
  • Name: descriptive name for the connection
  • Prefix: tool prefix (e.g., mytools → mytools_function_name)
4

Configure transport

Set up the connection transport:
  • Transport Type: Server-Sent Events
  • URL: your MCP server endpoint
  • Timeout: connection timeout (default: 5 seconds)
  • SSE Read Timeout: event stream timeout (default: 30 seconds)
5

Add environment variables

Configure any required environment variables:
  • API keys
  • Authentication tokens
  • Custom configuration
6

Test & create

Test the connection and save. CloudThinker shows a Connected status when the server responds correctly.

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Connection details

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Example MCP server

A simple MCP server that provides a weather lookup tool:
Once connected with prefix weather, agents can call:

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Use cases

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Custom data sources

Connect proprietary databases or APIs:
  • Internal metrics systems
  • Custom monitoring tools
  • Business intelligence platforms

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Specialized tools

Add domain-specific capabilities:
  • Custom compliance checks
  • Internal automation scripts
  • Legacy system integrations

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External services

Integrate third-party services:
  • Communication platforms
  • Ticketing systems
  • Cloud services not built-in

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Best practices

  • HTTPS endpoints — expose your MCP server only over HTTPS.
  • Rotate API keys — rotate credentials stored in environment variables on your normal schedule.
  • Implement authentication — validate incoming requests from CloudThinker before processing.
  • Set appropriate timeouts — tune Timeout and SSE Read Timeout to match your server’s response characteristics.
  • Monitor server health — track error rates and latency so connection drops are caught early.
  • Handle errors gracefully — return structured MCP error responses rather than crashing the server.

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Troubleshooting

Verify the MCP server is running, check network connectivity, increase timeout values, and confirm the firewall allows traffic.
Verify the prefix is set correctly, check that the MCP server returns tool definitions, ensure the protocol version is compatible, and review server logs for errors.
Verify environment variables are set correctly, check that API keys are valid, and ensure the server validates credentials correctly.
Increase the SSE read timeout, check for proxy interference, verify the server sends keepalive events, and review network stability.

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Security

  • Least privilege — grant only the permissions the agents need for your use case; start read-only and widen later.
  • Read-only by default — use read-only credentials unless you want agents to make changes through this connection.
  • Rotate credentials — rotate keys and tokens on your normal schedule; CloudThinker picks up the new value when you update the connection.
  • Revoke on offboarding — remove the credential at the provider when you delete a connection or a teammate leaves.
  • HTTPS endpoints — expose your MCP server only over HTTPS and validate the CloudThinker request origin.
  • Scoped credentials — store API keys and tokens in environment variables rather than hardcoding them in server code.

Overview

All connection types

Agents

How agents use connections