SEC XBRL (Financial Reporting) MCP Server for LlamaIndexGive LlamaIndex instant access to 4 tools to Get Company Concept, Get Company Facts, Get Submissions, and more

Name: SEC XBRL (Financial Reporting)
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add SEC XBRL (Financial Reporting) as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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The SEC XBRL (Financial Reporting) MCP Server for LlamaIndex is a standout in the Data Management category — giving your AI agent 4 tools to work with, ready to go from day one.

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python

import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to SEC XBRL (Financial Reporting). "
            "You have 4 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in SEC XBRL (Financial Reporting)?"
    )
    print(response)

asyncio.run(main())

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About SEC XBRL (Financial Reporting) MCP Server

Connect your AI agent to the SEC EDGAR database and perform deep financial analysis using standardized XBRL data. This server provides programmatic access to the U.S. Securities and Exchange Commission's public filing infrastructure.

LlamaIndex agents combine SEC XBRL (Financial Reporting) tool responses with indexed documents for comprehensive, grounded answers. Connect 4 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

Filing History — Retrieve the complete submission history for any entity using its Central Index Key (CIK)
Company Facts — Fetch the entire dictionary of XBRL facts reported by a company, covering all taxonomies (US-GAAP, IFRS, etc.)
Concept Analysis — Drill down into specific financial concepts (e.g., Net Income, Assets) for a single company over time
Market-Wide Frames — Aggregate specific financial data points across all reporting entities for a particular period and unit

The SEC XBRL (Financial Reporting) MCP Server exposes 4 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 4 SEC XBRL (Financial Reporting) tools available for LlamaIndex

When LlamaIndex connects to SEC XBRL (Financial Reporting) through Vinkius, your AI agent gets direct access to every tool listed below — spanning xbrl, financial-reporting, sec-edgar, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

get

Get company concept on SEC XBRL (Financial Reporting)

Get all XBRL disclosures for a single company concept

get

Get company facts on SEC XBRL (Financial Reporting)

Get all company concepts data for a specific company

get

Get submissions on SEC XBRL (Financial Reporting)

Includes metadata and recent filings. Get filing history for a specific entity

get

Get xbrl frames on SEC XBRL (Financial Reporting)

Get aggregated facts for a specific concept and period

Connect SEC XBRL (Financial Reporting) to LlamaIndex via MCP

Follow these steps to wire SEC XBRL (Financial Reporting) into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 4 tools from SEC XBRL (Financial Reporting)

Why Use LlamaIndex with the SEC XBRL (Financial Reporting) MCP Server

LlamaIndex provides unique advantages when paired with SEC XBRL (Financial Reporting) through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine SEC XBRL (Financial Reporting) tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain SEC XBRL (Financial Reporting) tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query SEC XBRL (Financial Reporting), a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what SEC XBRL (Financial Reporting) tools were called, what data was returned, and how it influenced the final answer

SEC XBRL (Financial Reporting) + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the SEC XBRL (Financial Reporting) MCP Server delivers measurable value.

Hybrid search: combine SEC XBRL (Financial Reporting) real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query SEC XBRL (Financial Reporting) to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying SEC XBRL (Financial Reporting) for fresh data

Analytical workflows: chain SEC XBRL (Financial Reporting) queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for SEC XBRL (Financial Reporting) in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with SEC XBRL (Financial Reporting) immediately.

"Get the filing history for Microsoft using CIK 789019."

"Show me all XBRL facts reported by Apple (CIK 320193)."

"Compare the 'AccountsPayableCurrent' for all companies in USD for the period CY2023Q3."

Troubleshooting SEC XBRL (Financial Reporting) MCP Server with LlamaIndex

Common issues when connecting SEC XBRL (Financial Reporting) to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

SEC XBRL (Financial Reporting) + LlamaIndex FAQ

Common questions about integrating SEC XBRL (Financial Reporting) MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query SEC XBRL (Financial Reporting) tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.

Does LlamaIndex support async MCP calls?

Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.

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