How to Use the FeedBlitz MCP in LlamaIndex

Q: Can LlamaIndex index FeedBlitz metrics for RAG?

Yes, you can load data from listmetrics and write it to your vector store. This lets your agent answer complex questions about your FeedBlitz campaign performance using semantic search.

Q: Does the LlamaIndex integration support filtering FeedBlitz MCP tools?

Yes, you can use the allowedtools filter when setting up the McpToolSpec. This lets you restrict your agent to read-only tools like getsubscriber while hiding modification tools.

Q: How do I handle large subscriber lists in LlamaIndex?

You can paginate through your subscribers using listsubscribers to avoid memory limits. LlamaIndex processes these records in chunks before indexing them into your vector database.

Index your FeedBlitz syndication metrics and subscriber data directly into LlamaIndex vector stores.

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Connect FeedBlitz MCP to LlamaIndex

Create your Vinkius account to connect FeedBlitz 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.

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Setup FeedBlitz with LlamaIndex

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Index FeedBlitz subscriber data for semantic search

The `list_subscribers` tool pulls your active reader list from FeedBlitz so LlamaIndex can index the raw metadata. This tool lets your RAG pipeline search subscriber profiles to find patterns in user engagement without manual exports. By feeding this data into a LlamaIndex vector store, your agent can query subscriber segments using natural language. This turns a flat list of emails into a searchable knowledge base of your audience.

Query FeedBlitz syndication details with LlamaIndex

The `get_syndication` tool retrieves structural details about your FeedBlitz RSS feeds and mailing lists for LlamaIndex indexing. LlamaIndex uses this information to ground its answers when you ask about your current newsletter configurations. Your LlamaIndex RAG application can cross-reference these feed settings with your published blog posts. This ensures your agent always knows exactly which RSS feeds are active and how they are configured.

Build a performance engine with this MCP Server

The `list_metrics` tool retrieves raw delivery and click data directly from your FeedBlitz campaigns to feed LlamaIndex. LlamaIndex indexes these metrics, allowing you to run semantic queries against your past newsletter performance. Instead of looking at static charts, you can ask your LlamaIndex agent which topics drove the most clicks last month. The agent queries the indexed metrics to deliver an answer grounded in your actual campaign history.

Setup guide

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by FeedBlitz. 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 FeedBlitz MCP in LlamaIndex

You use the llama-index-tools-mcp package to initialize the BasicMCPClient. From there, wrap it in McpToolSpec to expose tools like `list_syndications` to your FunctionAgent.

Yes, you can load data from `list_metrics` and write it to your vector store. This lets your agent answer complex questions about your FeedBlitz campaign performance using semantic search.

Yes, you can use the allowed_tools filter when setting up the McpToolSpec. This lets you restrict your agent to read-only tools like `get_subscriber` while hiding modification tools.

You can paginate through your subscribers using `list_subscribers` to avoid memory limits. LlamaIndex processes these records in chunks before indexing them into your vector database.

Your subscriber email addresses and feed configurations are processed in an ephemeral, zero-trust V8 sandbox. This prevents exposure of your FeedBlitz credentials and ensures your audience data remains private.

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