How to Use the Scoro MCP in LlamaIndex

Q: Can I use LlamaIndex to search through Scoro contacts?

Yes, you can use LlamaIndex to query listcontacts and index the results. This allows your agent to perform semantic searches over your entire customer list to find relevant companies or people.

Q: Does LlamaIndex support filtering specific Scoro tools?

Yes, you can use the allowedtools filter in LlamaIndex to restrict your agent's access. For instance, you can expose listtimeentries while blocking access to sensitive financial tools like listinvoices.

Q: How does semantic search work with Scoro project data?

LlamaIndex takes the JSON outputs from listprojects and converts them into vector embeddings. When you search for "overdue work," the engine matches the semantic meaning against those project descriptions.

Index your Scoro project tasks and invoices into LlamaIndex vector stores for search grounded in real business data.

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Connect Scoro MCP to LlamaIndex

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Setup Scoro with LlamaIndex

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Index Scoro Work Records into LlamaIndex

This data indexing tool turns your Scoro tool outputs into a searchable knowledge base. By running `list_tasks` and `list_projects`, LlamaIndex indexes your active work items directly into your local vector store. This stops your agent from guessing or relying on stale data. Your queries pull directly from live Scoro records, ensuring your RAG applications are always grounded in actual project states.

Analyze Historical Financial Trends

This financial indexing tool feeds your transaction history into your vector index by querying `list_invoices` and `list_expenses`. This MCP Server lets your agent retrieve past financial transactions and index them for semantic search. You can ask your agent complex questions about spending trends or client billing histories. The framework matches your natural language queries with the indexed financial payloads to find the exact records.

Query Team Activity and Audits

This audit tool gets a clear view of organizational changes by indexing the output of `list_activities` and `list_users`. LlamaIndex maps these activity logs to help you trace who completed specific tasks and when. Instead of scrolling through endless audit logs, you query your indexed data to find patterns. It makes tracking operational changes across your Scoro workspace fast and intuitive.

Setup guide

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

Yes, you can use LlamaIndex to query `list_contacts` and index the results. This allows your agent to perform semantic searches over your entire customer list to find relevant companies or people.

Install the llama-index-tools-mcp package and initialize the BasicMCPClient to connect your MCP server to your workflow. Convert the tools using McpToolSpec and pass them to your LlamaIndex FunctionAgent.

Yes, you can use the allowed_tools filter in LlamaIndex to restrict your agent's access. For instance, you can expose `list_time_entries` while blocking access to sensitive financial tools like `list_invoices`.

LlamaIndex takes the JSON outputs from `list_projects` and converts them into vector embeddings. When you search for "overdue work," the engine matches the semantic meaning against those project descriptions.

Your calendar events and task descriptions are processed entirely in memory or stored in your own designated vector database. Vinkius operates as a stateless proxy for your MCP connection, meaning your Scoro calendar and task data is never saved or analyzed on our servers.

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