Purpose
Provide a short reference for connecting an AI platform to an approved external data source through MCP. This acts as an auxiliary guide to the authoritative [[AIPM Playbook: MCP Connector Setup & Integration Configuration]].
Use Cases
Use this when a requester needs an AI assistant to connect to a named external system, access live data, or activate an MCP server in [[Glean]], [[Claude]], or [[ChatGPT]].
Setup Flow
- Identify the exact source system, endpoint, intended users, and business use case.
- Confirm whether the system already has a native integration before introducing an MCP connector.
- Confirm the required admin credentials, API access, client configuration, and service-account involvement.
- Activate the connector separately in each relevant AI platform.
- Restrict access to the requester or an approved group where platform capabilities allow it.
- Remove or replace outdated connector versions when migrating.
- Test authentication, authorization, representative reads, and expected failure behavior end to end.
- Ask the requester to confirm successful use before closing the request.
Escalation and Decision Points
- If the connector requires a new custom action, automation, or material implementation, promote the work to APMT as a CB or CBX item.
- If the issue is caused by credentials, permissions, or an agent-version mismatch, resolve or route it through the relevant owner.
- Involve Security, Legal / Compliance, or Corporate IT when the connector exposes sensitive data or requires enterprise credentials.
Guardrails
- Scope access to the smallest practical audience and data set.
- Do not put credentials or secrets in tickets, prompts, repositories, or shared documentation.
- Keep the requestor-facing AIPM record linked to any APMT delivery item.
- Document the connected system, platform, owner, and validation result without recording secret values.