u/Significant_Field573

Our team is building a Copilot Studio agent in Microsoft Teams with around 70 tools across Jira, Confluence, Bitbucket, Databricks and Neo4j.

It can:

• Create and update Jira tickets
• Check pull requests
• Run approved Neo4j queries
• Retrieve Databricks job details
• Create Confluence pages
• Combine information across multiple systems

We also use Power Automate to notify Teams when Databricks jobs fail, so the long-term idea is for the agent to investigate incidents and take follow-up actions.

My main concern is context and maintainability.

In GitHub Copilot, I use local MCPs together with repository instructions, documentation, skills, prompts and guardrails. The agent already understands the codebase and project context.

In Teams, even with 70 tools, the agent may not automatically know:

• Which repository belongs to a Databricks job
• Which Jira project owns a pipeline
• Which Confluence runbook is relevant
• Whether the user means DEV, PREPROD or PROD

I am also unsure whether exposing 70 tools to one agent will cause tool-selection, security, testing and maintenance issues.

Would it be better to use an orchestrator with specialized agents for Jira, documentation, source control and data platforms?

For people using Copilot Studio in production:

• How many tools does your agent have?
• Does reliability decrease as the tool count grows?
• How do you manage project context and permissions?
• Do users still need to provide a lot of context manually?
• Is this architecture worth continuing to invest in?

My current view is that Copilot Studio is useful for shared operational workflows, while GitHub Copilot remains better for repository-aware coding and debugging.