I'm doing the same thing now (with Slack as a medium of interaction with the agent) --- but not with MCP, just with straight up tool call APIs.
At Stainless we use https://github.com/dgellow/mcp-front to make it easy for anyone on the team (including non-technical folks) to OAuth into a pretty wide variety of tools for their AI chats, using their creds. All proxied on infra we control.
Even our read replica postgres DB is available, just push a button.
MCP is an inter-process (or inter-system) communication standard, and it's extremely successful at that. But some people try to shoehorn it into a single system where it makes for a cumbersome fit, like having your service talk to itself via MCP as a subprocess just for the sake of "hey, we have MCP".
If you own your loop AND your business logic lives in the same codebase/process as your agent loop, you don't need MCP at all, period. Just use a good agent framework like PydanticAI, define your tools (and have your framework forward your docstrings/arguments into the context) and you're golden!
https://ai.pydantic.dev/agents/#introduction
If you need professional help in any of this, I also do consulting and/or can do mentoring on my knowledge in this area.