watsonx Discovery MCP Server for LlamaIndex 6 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add watsonx Discovery as an MCP tool provider through the 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 watsonx Discovery. "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in watsonx Discovery?"
)
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 watsonx Discovery MCP Server
Connect your IBM watsonx Discovery account to any AI agent and harness the power of cognitive search and NLP-driven text analytics through natural conversation.
LlamaIndex agents combine watsonx Discovery tool responses with indexed documents for comprehensive, grounded answers. Connect 6 tools through the 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
- Cognitive Search — Perform natural language or Discovery Query Language (DQL) queries against your data collections for high-quality semantic search
- Data Discovery — Browse and list all data collections within your project to retrieve collection and document IDs
- Document Analysis — Retrieve comprehensive metadata, ingestion status, and technical details for specific indexed documents
- NLP Enrichments — List and monitor available enrichments (NLP models) like Sentiment, Entities, and Keywords being applied to your data
- Component Health — Verify project-level configurations, ingestion notices, and health settings for all project components
- Semantic Insights — Surface relevant information and hidden patterns from massive unstructured datasets through simple chat commands
The watsonx Discovery MCP Server exposes 6 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 watsonx Discovery to LlamaIndex via MCP
Follow these steps to integrate the watsonx Discovery 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 6 tools from watsonx Discovery
Why Use LlamaIndex with the watsonx Discovery MCP Server
LlamaIndex provides unique advantages when paired with watsonx Discovery through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine watsonx Discovery tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain watsonx Discovery tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query watsonx Discovery, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what watsonx Discovery tools were called, what data was returned, and how it influenced the final answer
watsonx Discovery + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the watsonx Discovery MCP Server delivers measurable value.
Hybrid search: combine watsonx Discovery real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query watsonx Discovery 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 watsonx Discovery for fresh data
Analytical workflows: chain watsonx Discovery queries with LlamaIndex's data connectors to build multi-source analytical reports
watsonx Discovery MCP Tools for LlamaIndex (6)
These 6 tools become available when you connect watsonx Discovery to LlamaIndex via MCP:
get_component_settings
Retrieves the configuration and health settings for project components
get_document_details
Retrieves metadata and status for a specific indexed document
list_available_enrichments
g., Sentiment, Entities) are being applied to documents. Lists all enrichments (NLP models) configured for the project
list_collection_documents
Lists all documents indexed within a specific collection
list_discovery_collections
Lists all data collections within the current watsonx Discovery project
query_discovery_content
Provide a collection ID and the query text. Performs a natural language or DQL query against a discovery collection
Example Prompts for watsonx Discovery in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with watsonx Discovery immediately.
"List all my Discovery collections."
"Search the 'Legal Documents' collection for 'contract termination clauses'."
"What enrichments are currently active in my project?"
Troubleshooting watsonx Discovery MCP Server with LlamaIndex
Common issues when connecting watsonx Discovery to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpwatsonx Discovery + LlamaIndex FAQ
Common questions about integrating watsonx Discovery 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 watsonx Discovery 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 watsonx Discovery to LlamaIndex
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.