Glean MCP for AI. Find answers across all company apps, instantly.
Works with every AI agent you already use
…and any MCP-compatible client








How this MCP server connects to your AI agent
Glean MCP unifies your entire company's knowledge base into one conversational interface. Ask anything—about a policy in Confluence, a discussion in Slack, or an employee's expertise profile—and it pulls accurate answers from every connected app instantly.
What AI agents can do with Glean Automation
Autocomplete
Provides intelligent suggestions as you type into the search bar.
Bulk index documents
Processes and adds large batches of documents to your knowledge base for searching.
Chat
Allows you to hold a natural conversation with the AI assistant based on your company's data.
Ask a single question and get results pulled from Slack, Jira, Confluence, and other connected services.
Find specific employees within your company based on their job title, department, or skill set.
Programmatically index new documents, delete old ones, and retrieve metadata for content management.
Target your search to a specific application, like Confluence or Drive, when you need focused results.
Ask an AI about this
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What AI agents can do with Glean: 12 Tools for Enterprise Search
These tools give your AI client granular control to manage documents, find people, or run deep searches across all of your connected applications.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Glean on VinkiusAutocomplete
Provides intelligent suggestions as you type into the search bar.
Bulk Index Documents
Processes and adds large batches of documents to your knowledge base for searching.
Chat
Allows you to hold a natural conversation with the AI assistant based on your...
Check Glean Status
Verifies that all connected applications are online and available for search.
Delete Document
Removes specific documents from the index when they are outdated or obsolete.
Get Collection
Retrieves detailed information about a specific curated set of content.
Get Document
Fetches the full details and metadata for an individual document by its ID.
Index Document
Adds a single, new document into the searchable knowledge base.
List Collections
Lists all the curated content collections available in your organization's knowledge...
Search By Datasource
Narrows a search to only look at data from one specific connected application, like...
Search People
Searches your employee directory for people using criteria like job title or...
Search
Performs a comprehensive search across every connected piece of content in the organization.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Glean, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,100+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Glean. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
Built on the Model Context Protocol (MCP) for Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 12 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
The pain of constant tab-switching, Solved with Vinkius AI Gateway
Today, finding an answer requires you to open five different browser tabs. You start in Confluence for the general policy, jump to Slack to see if anyone discussed it last week, then check Jira tickets to see which team owns the fix, and finally pull up Google Drive just to find the original requirements document. It’s a manual scavenger hunt that kills productivity.
With this MCP, you ask your agent one question—for example, 'What was decided on the API endpoint?' The system pulls data from Confluence for policy details, Slack for discussion context, and Jira for the assigned owner. You get a single, consolidated answer without ever clicking off your primary workspace.
Get unified answers with Glean MCP
The process of manually tracking down who owns a topic or where a decision was documented disappears. You don't waste time checking multiple dashboards; you just ask the agent to find the right person using `search_people` and it hands over their profile details.
What changes is this: your AI client acts as a single, unified layer sitting atop all of your corporate data. It doesn't care if the information started in Slack or Google Drive; it just answers.
What your AI can actually do with this
Dealing with siloed corporate data is exhausting. You know the answer exists somewhere, but finding it means jumping between Jira tickets, Confluence pages, and Google Drive folders. This MCP lets your AI client treat all that scattered knowledge like one single source of truth. Instead of performing multiple searches or toggling tabs, you ask a natural language question once.
The system then cross-references documents, conversations, and people profiles across all connected platforms to generate an answer grounded in your organization's actual content. When you connect this MCP through Vinkius, your AI client gets access to the whole catalog of enterprise data, letting you stop searching for information and start acting on it.
019dd0fb-24fd-7369-9ba8-cc1c216b2cbb Here's how it actually works
The bottom line is that you use this MCP to turn disparate corporate documents and conversations into one searchable knowledge graph for your AI agent.
Subscribe to this MCP and paste your Glean API Token into the Admin Console.
Your AI client connects to the service using the token. The system verifies connectivity, ensuring all data sources are available.
You type a question into your agent—whether it's 'Who is running the Payments team?' or 'What was decided about Feature X last week?'—and get an immediate, unified answer.
Who is this actually for?
This connector is essential for any employee who spends half their day context switching between documentation, chat logs, and project management tools just to find a single piece of information.
Uses this MCP to search across old Confluence wikis and new Jira tickets simultaneously when drafting an update guide.
Asks the agent about key decisions related to a feature, getting answers from both Slack threads and final documented requirements in Google Drive.
Uses the people search tool to find an employee's department or expertise before guiding them to the correct policy document in Confluence.
What Changes When You Connect
Stop switching between tools. Instead of opening Jira for tickets and Confluence for policies, your AI client finds the answer in a single query, providing context from both sources at once.
The People Search tool lets you find colleagues by their actual expertise or department, eliminating guesswork when you need to loop in an expert who might be hard to track down.
Document management tools like index_document and bulk_index_documents let IT teams keep the knowledge base fresh. You add new policies or updated procedures without manual intervention.
It’s more than just search. By asking questions via the chat tool, your agent generates answers grounded in real data—it doesn't guess; it cites the source.
Need to narrow down a massive result set? The search_by_datasource tool lets you focus results only on Slack conversations if that’s where the answer lives.
See it in action
The new hire needs policy guidance
A new marketing associate asks their agent, 'What's our refund policy for enterprise clients?' The MCP uses its AI chat tool to pull the precise text from the Customer Policy Handbook in Confluence and delivers it immediately.
The PM needs a team expert
A Product Manager asks, 'Who is the best person to talk to about payment processing?' The agent uses search_people to identify James Rodriguez as the Senior Engineering Manager, linking him directly into the conversation.
The engineer needs audit context
An engineering team member asks, 'What were the key discussion points about PCI compliance?' The agent uses search across Slack and documentation to pull three relevant threads from multiple sources for review.
The honest tradeoffs
Using a single search engine
Opening Google Drive, searching the document name. Then opening Jira, using keywords in the description field. This takes 5 minutes and requires copy-pasting results into email.
Use this MCP's search tool to ask, 'Where is the deployment runbook for Q2?' The answer will automatically surface relevant links from Confluence and Google Drive without you ever leaving your agent interface.
Manually indexing documents
A team member saves a new policy as a PDF and emails it to the group, hoping someone remembers to upload it somewhere searchable.
Use index_document or bulk_index_documents programmatically. The system handles adding that knowledge immediately, ensuring everyone can ask questions about it right away.
When It Fits, When It Doesn't
You need this MCP if your company's knowledge is spread across 3 or more different platforms (e.g., Slack, Jira, Confluence, Google Drive). If you only use one tool for everything, a basic search engine will work fine. But since the truth lives in conversations and documents scattered everywhere, you need the universal cross-referencing capability this MCP provides. Use it when you need to know who knows something or where a decision was made—not just what the answer is. Don't use it if your data sources are already centralized into one single database; then, a direct API connection might be enough.
Questions you might have
Can Glean MCP find policies from old Confluence pages? +
Yes, absolutely. The MCP searches all connected sources, including deep archives in Confluence and other wikis. It surfaces the policy even if it hasn't been updated recently.
Does Glean MCP search private Slack conversations? +
It searches across all connected chat platforms like Slack. As long as the data source is connected, your agent can find relevant discussions based on keywords or context.
How do I update content using Glean MCP? +
You have two options: use index_document to add a single new file, or use bulk_index_documents if you're adding an entire batch of updated policy manuals.
Is the search limited to just documents? +
No. The MCP is designed for universal knowledge. It searches not only documents but also conversations and employee profiles using search_people.
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