How to Use the Good Grants MCP in AutoGen

Q: Can AutoGen agents write new Good Grants applications?

Yes, an agent can initiate createnewapplication once the group consensus is reached. The writer agent drafts the content, and the validator agent executes the tool to submit it.

Q: How do AutoGen agents handle conflicting Good Grants reviews?

When listapplicationreviews returns mixed feedback, your critic agent highlights the negative reviews. The writer agent then modifies the application draft to address those specific concerns.

Enable AutoGen agents to debate, review, and collaborate on Good Grants applications automatically.

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Connect Good Grants MCP to AutoGen

Create your Vinkius account to connect Good Grants to AutoGen 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 Good Grants with AutoGen

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Let AutoGen agents debate grant opportunities

Your AutoGen agents collaborate by querying `list_grant_funds` to identify potential funding sources. A financial agent evaluates the fund sizes while a program agent matches them against your organization's mission. They debate the viability of each option using data pulled from `list_grant_categories`. This group consensus ensures you only spend time on opportunities that fit your strategic goals.

Run multi-agent reviews via this MCP Server

This MCP Server allows a writer agent to draft a proposal using `create_new_application` while a reviewer agent criticizes it. The reviewer pulls historical feedback using `list_application_reviews` to find potential weaknesses. They pass the draft back and forth, refining the text until both agents agree it meets the guidelines. You only see the final, optimized draft once the debate concludes.

Coordinate team assignments and application details

Your coordinator agent runs `list_account_users` to see who on your team is qualified to manage a new submission. This MCP Server helps your coordinator agent retrieve the exact submission fields using `get_application_details` to assign tasks. The agents handle the administrative work of matching people to requirements. This keeps your team organized without requiring manual coordination in the portal.

Setup guide

Set up Good Grants MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Good Grants tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Good Grants_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Good Grants data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Good Grants_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Good Grants data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Good Grants. 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.

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Common questions about Good Grants MCP in AutoGen

Use the AutoGen MCP tool adapter to convert the server's tools into the schema AutoGen expects. Pass them to your AssistantAgent constructor to let the agent use `list_grant_funds` during conversations.

Yes, an agent can initiate `create_new_application` once the group consensus is reached. The writer agent drafts the content, and the validator agent executes the tool to submit it.

When `list_application_reviews` returns mixed feedback, your critic agent highlights the negative reviews. The writer agent then modifies the application draft to address those specific concerns.

Yes, you can connect using the Streamable HTTP transport parameters. This allows your multi-agent system to communicate with the Vinkius managed endpoint over a secure web connection.

All review data retrieved via the MCP server is transmitted over an encrypted TLS connection. The Vinkius runtime executes in an ephemeral sandbox, meaning your evaluation records are never cached or exposed to other users.

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