How to Use the Confido Legal MCP in LlamaIndex

Q: Can LlamaIndex query Confido Legal payment history?

Yes, by indexing the results of listpaymentlinks, your application can answer questions about historical payment trends. The agent performs semantic searches over the retrieved records.

Q: Can I filter Confido Legal tools in LlamaIndex?

You can use the allowedtools filter to restrict which operations the agent performs. This limits access and keeps your indexing focused on specific financial tasks.

Index your Confido Legal data into LlamaIndex for grounded, searchable financial intelligence.

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Connect Confido Legal MCP to LlamaIndex

Create your Vinkius account to connect Confido Legal 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 Confido Legal with LlamaIndex

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Build a RAG index for Confido Legal

Run `list_subscriptions` to feed your current billing cycle data into a vector store. LlamaIndex then makes these records searchable for your Q&A applications. This turns your static accounting data into a live knowledge base. Your agent answers questions about past payments by querying the index instead of guessing.

Ground answers in Confido Legal data

Use `get_payment_link_details` to pull specific record information into your RAG pipeline. The agent retrieves the exact status of a link to provide accurate, up-to-date responses. This prevents the agent from hallucinating financial figures. It reads the live API data first, then summarizes the status for the user.

Query legal matters with LlamaIndex

Call `list_matters` to populate your index with active legal case data. You can filter these results by client ID to narrow down your search scope. Your agent uses this context to ground its reasoning during complex document reviews. It finds the right case details instantly without manual searching.

Setup guide

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

Use the MCP tool spec to convert our tools into a format LlamaIndex can ingest. Once connected, your agent treats the output as a searchable data source.

Yes, by indexing the results of `list_payment_links`, your application can answer questions about historical payment trends. The agent performs semantic searches over the retrieved records.

It does, as our tools are fully compatible with FunctionAgent setups. You simply pass the tool list and let the agent handle the indexing logic.

You can use the allowed_tools filter to restrict which operations the agent performs. This limits access and keeps your indexing focused on specific financial tasks.

Your financial data is processed in a zero-trust, ephemeral sandbox. No data is stored permanently outside our secure infrastructure, and every query is scrubbed after the session ends.

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