How to Use the Agendor MCP in LlamaIndex

Q: Can I filter which Agendor tools LlamaIndex sees?

Yes, you can use the allowedtools filter to limit the agent's access. This ensures your agent only uses the specific CRM capabilities you want it to have.

Index your Agendor sales data into LlamaIndex for grounded, searchable insights.

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Connect Agendor MCP to LlamaIndex

Create your Vinkius account to connect Agendor 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 Agendor with LlamaIndex

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Index Agendor records with LlamaIndex

Turn your CRM into a searchable knowledge base. The `list_people` tool provides the raw data that LlamaIndex converts into a vector store for semantic retrieval. Your agents answer questions about specific leads by searching this index. It prevents hallucinations by grounding every answer in the actual data pulled from your CRM.

Query your sales pipeline natively

Ask your agent about current progress using natural language. The system executes `list_deals` and then indexes those opportunities, allowing you to ask questions like which deals are stalled in the negotiation phase. This approach maps API output to your vector store. It makes your CRM data queryable alongside your PDF reports and internal company wikis.

Automate CRM updates via RAG

Create a loop where your agent reads, analyzes, and updates your CRM. After the agent reviews tasks from `list_tasks`, it updates the index to reflect current priorities. Use `create_person` to push new findings back into your CRM after the agent synthesizes information from your documents. This keeps your knowledge base and your sales system in sync.

Setup guide

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

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Common questions about Agendor MCP in LlamaIndex

Use the MCP tool spec to connect the server to your LlamaIndex workflow. Once connected, your agent can call tools and index the results into your local vector store.

Absolutely. By passing the tools to your FunctionAgent, you allow the model to decide when to call the CRM tools to get the data it needs to answer your query.

Yes, you can use the allowed_tools filter to limit the agent's access. This ensures your agent only uses the specific CRM capabilities you want it to have.

Your index persists according to your LlamaIndex configuration. The MCP Server provides the fresh data, and your vector store maintains the history of those lookups.

We use scoped tokens to ensure only your specific LlamaIndex instance can reach your CRM data. All interactions with your lead and organizational records are encrypted in transit.

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