Glean MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Glean through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Glean "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Glean?"
)
print(result.data)
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 enterprise account to any AI agent and take full control of your corporate-wide knowledge discovery and AI-powered workspace through natural conversation.
Pydantic AI validates every Glean tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
What you can do
- Corporate Discovery Orchestration — Identify bounded CRM records and extract explicitly attached REST arrays targeting
/searchto find knowledge mapped across all SaaS applications natively - Live AI Answer Retrieval — Enumerate explicitly attached structured rules to fire RAG mechanisms, returning pure AI-generated blocks distilled from your company data limitlessly
- Multi-Source Filtering — Perform structural extraction of properties by hardcoding explicit filters parsing only specific datasources like Jira, Confluence, or Slack nodes synchronousy
- People & Identity Discovery — Retrieve corporate active directory information, matching user skills, roles, and names directly to generate hard customer bindings natively
- Intelligent Chat Orchestration — Commands explicit REST targets checking
/chatto manage ongoing text streams while maintaining historical thread mapping for complex reasoning - Knowledge Ingestion & Indexing — Upload massive custom text properties directly routing into corporate search logic to verify internal documentation boundaries securely
- Predictive Autocomplete — Discovers disconnected physical limits executing
/autocompleteto predict precise page destinations from partial prefixes flawlessly - Data Deletion Oversight — Explains explicitly mapped arrays checking
/deleteto remove indexed documents permanently and block future retrieval vectors
The Glean MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Glean to Pydantic AI via MCP
Follow these steps to integrate the Glean MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from Glean with type-safe schemas
Why Use Pydantic AI with the Glean MCP Server
Pydantic AI provides unique advantages when paired with Glean through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Glean integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Glean connection logic from agent behavior for testable, maintainable code
Glean + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Glean MCP Server delivers measurable value.
Type-safe data pipelines: query Glean with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Glean tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Glean and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Glean responses and write comprehensive agent tests
Glean MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Glean to Pydantic AI via MCP:
autocomplete
Retrieve explicit Cloud logging tracing explicit Vault limits
chat_completion
Dispatch an automated validation check routing explicit Gateway history
custom_request
` merging physical POST arrays strictly. Identify precise active arrays spanning native Hold parsing
delete_document
Inspect deep internal arrays mitigating specific Plan Math
get_answer
Enumerate explicitly attached structured rules exporting active Billing
get_suggestions
Irreversibly vaporize explicit validations extracting rich Churn flags
index_document
Identify precise active arrays spanning native Gateway auth
search_datasource
g. Perform structural extraction of properties driving active Account logic
search_docs
Identify bounded CRM records inside the Headless Glean Platform
search_people
Provision a highly-available JSON Payload generating hard Customer bindings
Example Prompts for Glean in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Glean immediately.
"Search for 'Q2 hiring plan' in all apps"
"Who knows about 'React Native' in my company?"
"Get AI answer for: 'What is our expense policy for business travel?'"
Troubleshooting Glean MCP Server with Pydantic AI
Common issues when connecting Glean to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiGlean + Pydantic AI FAQ
Common questions about integrating Glean MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect Glean with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Glean to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.