Grain MCP Server for AutoGen 12 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Grain as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with McpWorkbench(
server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
transport="streamable_http",
) as workbench:
tools = await workbench.list_tools()
agent = AssistantAgent(
name="grain_agent",
tools=tools,
system_message=(
"You help users with Grain. "
"12 tools available."
),
)
print(f"Agent ready with {len(tools)} tools")
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 Grain MCP Server
Connect your Grain.com account to any AI agent and take full control of your team meeting recordings, automated transcriptions, and AI-powered insights through natural conversation.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Grain tools. Connect 12 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.
What you can do
- Meeting Orchestration — List all meeting recordings in your workspace and retrieve primary entry points for workspace interactions natively
- Live Detail Retrieval — Resolve deep specific objects including transcripts and speaker attribution mapped by recording ID flawlessly
- AI Transcription — Download full text structures with speaker attribution, parsing raw linguistic data to review critical discussions limitlessly
- Contextual Insights — Extract high-level abstract reductions including sentiment mapping, summaries, and key takeaways generated by Grain's ML engines
- Action Item Tracking — Filter targeted follow-up tasks detected automatically within meeting scopes to automate post-call workflows
- Highlight Navigation — Identify curated clips and key moments generated by users within specific timestamps to focus on critical insights
- Global Search — Execute keyword scanning across all meeting recordings to find specific discussions and ranked datasets synchronously
- Asset Ingestion — Ingest remote video streams by passing public URLs for initial structural transformations and AI processing securely
- Team Oversight — Retrieve fully enumerated team maps tracking workspace members and authenticated user profiles natively
The Grain MCP Server exposes 12 tools through the Vinkius. Connect it to AutoGen 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 Grain to AutoGen via MCP
Follow these steps to integrate the Grain MCP Server with AutoGen.
Install AutoGen
Run pip install "autogen-ext[mcp]"
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Integrate into workflow
Use the agent in your AutoGen multi-agent orchestration
Explore tools
The workbench discovers 12 tools from Grain automatically
Why Use AutoGen with the Grain MCP Server
AutoGen provides unique advantages when paired with Grain through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Grain tools to solve complex tasks
Role-based architecture lets you assign Grain tool access to specific agents. a data analyst queries while a reviewer validates
Human-in-the-loop support: agents can pause for human approval before executing sensitive Grain tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Grain tool responses in an isolated environment
Grain + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Grain MCP Server delivers measurable value.
Collaborative analysis: one agent queries Grain while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Grain, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Grain data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Grain responses in a sandboxed execution environment
Grain MCP Tools for AutoGen (12)
These 12 tools become available when you connect Grain to AutoGen via MCP:
get_action_items
Extract all action items identified from a recording
get_current_user
Retrieve the authenticated Grain user profile
get_insights
Retrieve AI-generated insights from a recording
get_recording
Retrieve full details of a specific meeting recording
get_transcript
Retrieve the full timestamped transcript of a meeting with speaker names
list_highlights
List all highlights (curated clips) from a recording
list_recordings
List all meeting recordings in the Grain workspace
list_shared_clips
List all clips that have been shared from the workspace
list_tags
List all tags used across recordings and highlights
list_workspace_members
List all members of the Grain workspace
search_recordings
Search across all meeting recordings by keyword
upload_video
Upload an external video URL for processing by Grain
Example Prompts for Grain in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Grain immediately.
"List my meeting recordings from today"
"What were the key decisions in the 'Roadmap Sync' meeting?"
"Search for recordings mentioning 'pricing strategy'"
Troubleshooting Grain MCP Server with AutoGen
Common issues when connecting Grain to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Grain + AutoGen FAQ
Common questions about integrating Grain MCP Server with AutoGen.
How does AutoGen connect to MCP servers?
Can different agents have different MCP tool access?
Does AutoGen support human approval for tool calls?
Connect Grain 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.
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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 Grain to AutoGen
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.