What You’ll Find Here
Role-specific examples organized by job function, each including:- Common use cases: What teams actually accomplish with MCP
- Real prompts: Copy-paste examples you can try immediately
- Prerequisites: Required connectors and setup
- Best practices: Tips for getting better results
Getting Started
Before diving into role-specific examples, ensure you have:- MCP server configured: Use the MCP Configurator to install the MCP server in your MCP host
- Relevant connectors: Connect the data sources your team uses
- Appropriate permissions: Verify you can access the data sources you need
The effectiveness of these prompts depends on having the right data sources
connected. Each role section lists recommended connectors.
Examples by Role
Engineering
Debug errors, review PRs, understand code history, generate documentation
Product Management
Draft PRDs, track projects, analyze feedback, research competitors
Support
Triage tickets, find solutions, draft responses, identify knowledge gaps
Sales
Research accounts, prepare for calls, track deals, draft outreach
Data Analytics
Query databases, identify trends, generate reports, detect anomalies
Operations
IT troubleshooting, HR policies, meeting prep, incident response
How MCP Tools Work
When you use Glean’s MCP server, your AI assistant can:- Search Glean: Find relevant documents, conversations, and code across your company
- Read documents: Retrieve full content from specific URLs or IDs
- Query structured data: Access databases, spreadsheets, and data warehouses
- Find people: Look up employees and their areas of expertise
- Access email: Search Gmail or Outlook for relevant messages
- Chat with Glean: Ask Glean Assistant questions about your data
All MCP queries respect your existing permissions. You’ll only see data you
already have access to in Glean.
Prompting Tips
To get the most from Glean’s MCP server:Be Explicit About Tools
Tell your AI assistant to use Glean:- ✅ “Search Glean for recent PRs related to authentication”
- ✅ “Use Glean to find the design doc for feature X”
- ❌ “Tell me about authentication” (may not use MCP)
Specify Data Sources
Mention specific connectors when relevant:- ✅ “Search Glean for Zendesk tickets about login errors”
- ✅ “Find Slack conversations in #engineering about this bug”
- ❌ “Find tickets about login errors” (less specific)
Provide Context
Include relevant identifiers, dates, or keywords:- ✅ “Given Jira ticket EN-12345, find similar past issues”
- ✅ “Search for discussions about the Q3 roadmap in the last 30 days”
- ❌ “Find similar issues” (too vague)
Iterate and Refine
Start broad, then narrow based on results:- “Search Glean for information about our deployment process”
- Review what comes back
- “Now focus on the Kubernetes deployment docs from the last quarter”