How to Use the Good Grants MCP in LlamaIndex

Q: Can LlamaIndex agents search past Good Grants reviews?

Yes, by calling listapplicationreviews through this MCP Server, your agent can index historical review comments. You can then query the vector store to see common reasons for rejection or approval.

Q: How do I limit which Good Grants tools the LlamaIndex MCP integration can access?

Use the allowedtools filter when defining the McpToolSpec. You can restrict the agent to read-only tools like listgrantcategories and completely block write tools like createnewapplication.

Build RAG pipelines that index Good Grants data into vector stores for semantic search with LlamaIndex.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Good Grants MCP to LlamaIndex

Create your Vinkius account to connect Good Grants 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.

GDPR Free for Subscribers

Setup Good Grants with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Index active funds into LlamaIndex vector stores

Your LlamaIndex agent pulls live funding data using `list_grant_funds` and indexes it directly into your local vector database. This lets you run semantic searches over active opportunities instead of relying on basic keyword filters. By combining this search with `list_grant_categories`, your query engine retrieves highly relevant funding matches. You get answers grounded in real-time portal data, preventing hallucinated opportunities.

Query application history using this MCP Server

This MCP Server exposes your historical submissions by executing `list_applications` to feed your RAG pipeline. The agent indexes past proposals alongside their feedback retrieved via `list_application_reviews`. When you draft a new proposal, the query engine searches this index to find what worked in the past. Your agent uses actual historical feedback to guide your current writing strategy.

Retrieve user roles and application specs

Your agent queries `list_account_users` to verify which team members have access to specific funding programs. It then pulls the exact submission guidelines using `get_application_details` to build a localized context window. This integration ensures your agent always references up-to-date user permissions and application requirements. You avoid authorization errors before initiating `create_new_application`.

Setup guide

Set up Good Grants 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 Good Grants 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 Good Grants tools.",
)
response = await agent.run("List recent Good Grants data")

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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Good Grants now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Good Grants MCP in LlamaIndex

Connect using the LlamaIndex MCP tool spec and convert the tools to a tool spec. Your agent calls `list_grant_funds` to fetch the raw text, which LlamaIndex chunks and embeds into your vector database.

Yes, by calling `list_application_reviews` through this MCP Server, your agent can index historical review comments. You can then query the vector store to see common reasons for rejection or approval.

Use the allowed_tools filter when defining the McpToolSpec. You can restrict the agent to read-only tools like `list_grant_categories` and completely block write tools like `create_new_application`.

Yes, you can load the tools using the asynchronous method to prevent blocking your main query pipeline. This is ideal when pulling large lists of applications.

The MCP server processes your user directories and application details inside a sandboxed V8 Isolate. No data is stored, and the temporary credentials used to query `list_account_users` are discarded immediately after execution.

Use it with your favorite AI tools

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

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript