DocSumo MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add DocSumo 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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Vinkius supports streamable HTTP and SSE.
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 DocSumo. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in DocSumo?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About DocSumo MCP Server
Integrate DocSumo, the advanced Intelligent Document Processing (IDP) platform, directly into your AI workflow. Automate the extraction of complex data from invoices, bank statements, and ID cards, monitor your processing pipelines, and retrieve structured results using natural language.
LlamaIndex agents combine DocSumo tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Pipeline Oversight — List and retrieve detailed settings and processing statuses for all your document types and IDP workflows.
- Data Intelligence — Access the structured data extracted by DocSumo's AI engine, including table layouts and verified fields.
- Confidence Monitoring — Identify documents that require manual review due to low extraction confidence scores.
- Extraction Auditing — Retrieve a chronological feed of recent extraction results across all your processed document categories.
The DocSumo MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect DocSumo to LlamaIndex via MCP
Follow these steps to integrate the DocSumo MCP Server with LlamaIndex.
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 10 tools from DocSumo
Why Use LlamaIndex with the DocSumo MCP Server
LlamaIndex provides unique advantages when paired with DocSumo through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine DocSumo tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain DocSumo tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query DocSumo, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what DocSumo tools were called, what data was returned, and how it influenced the final answer
DocSumo + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the DocSumo MCP Server delivers measurable value.
Hybrid search: combine DocSumo real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query DocSumo 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 DocSumo for fresh data
Analytical workflows: chain DocSumo queries with LlamaIndex's data connectors to build multi-source analytical reports
DocSumo MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect DocSumo to LlamaIndex via MCP:
get_docsumo_account_metadata
Retrieve metadata and usage limits for your DocSumo account
get_document_extraction_data
Get the structured data extracted from a specific document
list_docsumo_document_types
List all document types (e.g., invoices, bank statements) configured in DocSumo
list_documents_awaiting_review
Identify documents that require manual review due to low extraction confidence
list_failed_doc_extractions
Identify documents that failed the extraction process (mock logic)
list_latest_extraction_results
Identify the most recently processed documents across all types
list_processed_documents
List all documents processed by DocSumo, optionally filtered by document type
list_successfully_parsed_docs
Identify documents that have been successfully processed and verified
quick_idp_health_audit
Retrieve a high-level summary of document processing activity and success rates
search_documents_by_filename
Search for processed documents using a filename keyword
Example Prompts for DocSumo in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with DocSumo immediately.
"List all processed bank statements."
"Show me the extraction results for document 'DOC-5544'."
"Are there any documents that failed to process today?"
Troubleshooting DocSumo MCP Server with LlamaIndex
Common issues when connecting DocSumo to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpDocSumo + LlamaIndex FAQ
Common questions about integrating DocSumo MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect DocSumo with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect DocSumo to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.