Glean MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Autocomplete, Bulk Index Documents, Chat, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Glean as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Glean app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Glean. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Glean?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Glean MCP Server
Connect your Glean workspace to any AI agent and unlock enterprise knowledge through natural conversation.
LlamaIndex agents combine Glean tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Universal Search — Search across all connected data sources (Confluence, Slack, Google Drive, Jira, and more) from a single query
- Datasource Filtering — Focus searches on a specific connected platform for targeted results
- People Search — Find employees by name, role, expertise, or department across your organization
- Document Management — Index new documents, bulk-index batches, retrieve document metadata, and remove outdated content
- Curated Collections — Browse and inspect curated content collections for onboarding, policies, and shared knowledge
- AI Chat — Ask questions to Glean's AI assistant, which generates answers grounded in your organization's knowledge base
- Autocomplete — Get intelligent search suggestions based on organizational knowledge as you type
The Glean MCP Server exposes 12 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 12 Glean tools available for LlamaIndex
When LlamaIndex connects to Glean through Vinkius, your AI agent gets direct access to every tool listed below — spanning enterprise-search, unified-search, people-discovery, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Autocomplete suggestions
Bulk index documents
AI chat
Verify connectivity
Delete a document
Get collection details
Get document details
Index a document
List collections
Search across all content
g., Confluence, Slack, Google Drive). Search in specific datasource
Search people
Connect Glean to LlamaIndex via MCP
Follow these steps to wire Glean into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Glean MCP Server
LlamaIndex provides unique advantages when paired with Glean through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Glean tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Glean tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Glean, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Glean tools were called, what data was returned, and how it influenced the final answer
Glean + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Glean MCP Server delivers measurable value.
Hybrid search: combine Glean real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Glean to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Glean for fresh data
Analytical workflows: chain Glean queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Glean in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Glean immediately.
"Search for our deployment runbook and the on-call rotation schedule."
"Ask the AI assistant: What is our company's refund policy for enterprise customers?"
"Find the engineering lead for the payments team and search Slack for recent discussions about PCI compliance."
Troubleshooting Glean MCP Server with LlamaIndex
Common issues when connecting Glean to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpGlean + LlamaIndex FAQ
Common questions about integrating Glean MCP Server with LlamaIndex.