How to Use the Platform.ly MCP in LlamaIndex

Q: How do I install the Platform.ly MCP Server for LlamaIndex?

Run pip install llama-index-tools-mcp and initialize BasicMCPClient to expose Platform.ly CRM tools to your LlamaIndex query engine.

Q: Can LlamaIndex query Platform.ly segments?

Yes, your LlamaIndex agent calls listprojectsegments to retrieve your Platform.ly segments and indexes them for semantic search queries.

Q: How does LlamaIndex avoid duplicate contacts in Platform.ly?

The LlamaIndex agent runs searchcontactbyemail before attempting to call createnewcontact to keep your Platform.ly directory clean.

Q: Does this MCP Server support LlamaIndex agent filtering?

Yes, you can use LlamaIndex's allowedtools filter to restrict which Platform.ly actions, like updateexistingcontact, the agent can perform.

Index your Platform.ly customer records directly into LlamaIndex to run semantic queries over actual sales data.

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Connect Platform.ly MCP to LlamaIndex

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Setup Platform.ly with LlamaIndex

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Semantic search over Platform.ly contacts

`list_crm_contacts` extracts your Platform.ly customer directory so LlamaIndex can turn raw profiles into searchable vector embeddings. Instead of guessing exact names, you can ask your LlamaIndex agent to find Platform.ly contacts who fit a general description. The LlamaIndex index updates dynamically, allowing you to query Platform.ly histories without waiting for manual exports. You get instant answers grounded in actual Platform.ly CRM data rather than generic LlamaIndex hallucinations.

Knowledge-augmented pipeline analysis with MCP

`list_sales_pipelines` feeds active Platform.ly deal stages directly into your LlamaIndex RAG application for instant analysis. Your LlamaIndex agent reads the Platform.ly pipeline structure, matches it with current deal values, and summarizes your sales pipeline health. This integration allows you to query your Platform.ly sales process using LlamaIndex natural language queries. The MCP Server ensures your LlamaIndex index always has the latest Platform.ly pipeline names and configurations.

Context-aware CRM note generation

`add_note_to_contact` lets your LlamaIndex agent append detailed summaries directly to Platform.ly customer records after analyzing long research documents. The LlamaIndex agent reads your uploaded PDF, extracts the key takeaways, and logs them to the Platform.ly contact timeline. To ensure the note goes to the right Platform.ly profile, the LlamaIndex agent first calls `get_contact_details` to verify the identity. This keeps your sales team aligned without requiring you to manually summarize and paste LlamaIndex research into Platform.ly.

Setup guide

Set up Platform.ly 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 Platform.ly 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 Platform.ly tools.",
)
response = await agent.run("List recent Platform.ly 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 Platform.ly. 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 Platform.ly MCP in LlamaIndex

Run `pip install llama-index-tools-mcp` and initialize `BasicMCPClient` to expose Platform.ly CRM tools to your LlamaIndex query engine.

Yes, your LlamaIndex agent calls `list_project_segments` to retrieve your Platform.ly segments and indexes them for semantic search queries.

The LlamaIndex agent runs `search_contact_by_email` before attempting to call `create_new_contact` to keep your Platform.ly directory clean.

Yes, you can use LlamaIndex's `allowed_tools` filter to restrict which Platform.ly actions, like `update_existing_contact`, the agent can perform.

Your Platform.ly contact details, notes, and pipeline stages are vectorized and stored locally in your chosen LlamaIndex index. Vinkius secures the MCP connection to the Platform.ly API, ensuring your CRM records are never leaked to external public indexers.

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