How to Use the Glean MCP in LlamaIndex

Q: Can LlamaIndex use Glean to search specific datasources?

Yes. Use searchbydatasource to target specific repositories like Google Drive without scanning the entire company index.

Q: Can I update the index automatically?

Use indexdocument to push updates into your flow. This keeps your local vector store in sync with the source of truth.

Q: How do I verify the server is active?

Call checkgleanstatus before your indexing job starts. It confirms the connection is live and the API is responsive.

Ground your LlamaIndex knowledge base in real-time company data with this MCP server.

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Connect Glean MCP to LlamaIndex

Create your Vinkius account to connect Glean to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Glean with LlamaIndex

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Claude

Perplexity

Vector-ready document indexing

Transform your enterprise files into a queryable knowledge base by piping results from `search` directly into your vector store. You create a unified index where live API data meets static documentation. This approach stops hallucinations dead in their tracks. The model answers questions based on the specific document content returned by `get_document` during the retrieval phase.

Unified knowledge retrieval

Fetch data from disparate sources like Confluence or Slack using `search_by_datasource`. You aggregate these results into a single index that LlamaIndex treats as a primary knowledge source. Your application queries this index to provide precise answers. It bypasses the need for manual file management by keeping the data structure updated via `index_document` calls.

Granular data access control

Filter which tools the agent can access using the tool list configuration. You restrict the agent to read-only operations like `search` and `get_collection` to maintain strict data integrity. This setup ensures the agent only interacts with the parts of your organization you explicitly approve. You maintain full control over the knowledge surface area.

Setup guide

Set up Glean MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Glean MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Glean tools.",
)
response = await agent.run("List recent Glean data")

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Common questions about Glean MCP in LlamaIndex

The tools act as data loaders. You fetch the content, index it, and the agent retrieves the relevant chunks for your RAG pipeline.

Yes. Use `search_by_datasource` to target specific repositories like Google Drive without scanning the entire company index.

Your documents remain within the enterprise scope. The server enforces ACLs so the agent only sees what you see.

Use `index_document` to push updates into your flow. This keeps your local vector store in sync with the source of truth.

Call `check_glean_status` before your indexing job starts. It confirms the connection is live and the API is responsive.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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