Swiftype 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 Swiftype 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 Swiftype. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Swiftype?"
)
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 Swiftype MCP Server
Empower your conversational AI with robust enterprise search capabilities by securely integrating the Swiftype (Elastic) MCP connector. Stop navigating web dashbaords to manage indexing logic; allow your LLM to act as a direct data architect interacting with your core Swiftype endpoints natively. With full support for reading, creating, and deleting JSON documents on the fly, inspecting live search engine queries, and querying direct analytical metrics like top clicks—this connector brings headless search administration straight to your preferred prompt environment.
LlamaIndex agents combine Swiftype 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
- Headless Search & Suggestions — Execute strict queries interrogating custom content engines running
st.post_searchand provide predictive autocompletes processingst.post_suggest. - CRUD Document Indexing — Pull exact active records from isolated data maps using
st.list_documents, inject new payload structures in bulk operatingst.create_documents, or vaporize explicit keys commandingst.delete_documents. - Architectural Discovery — Browse registered core scopes applying
st.list_enginesand parse schema blueprints identifying object hierarchies withst.list_doc_types. - Search Analytics & CTR — Uncover real-world operational user conversion intent evaluating actual volume via
st.analytics_top_searchesand calculating active hit paths invokingst.analytics_top_clicks.
The Swiftype 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 Swiftype to LlamaIndex via MCP
Follow these steps to integrate the Swiftype 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 Swiftype
Why Use LlamaIndex with the Swiftype MCP Server
LlamaIndex provides unique advantages when paired with Swiftype through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Swiftype tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Swiftype tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Swiftype, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Swiftype tools were called, what data was returned, and how it influenced the final answer
Swiftype + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Swiftype MCP Server delivers measurable value.
Hybrid search: combine Swiftype real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Swiftype 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 Swiftype for fresh data
Analytical workflows: chain Swiftype queries with LlamaIndex's data connectors to build multi-source analytical reports
Swiftype MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Swiftype to LlamaIndex via MCP:
st.analytics_top_clicks
Identify precise active arrays spanning native Hold parsing
st.analytics_top_searches
Inspect deep internal arrays mitigating specific Plan Math
st.create_documents
Enumerate explicitly attached structured rules exporting active Billing
st.delete_documents
json` eliminating cached pages permanently erasing bounds metrics from search. Dispatch an automated validation check routing explicit Gateway history
st.list_doc_types
json` extracting schema blueprints enforcing exact map types correctly. Retrieve explicit Cloud logging tracing explicit Vault limits
st.list_documents
json` dumping all stored metadata physically tracking IDs per document type. Irreversibly vaporize explicit validations extracting rich Churn flags
st.list_domains
json` verifying automated crawler limits mapped inside explicit index scopes. Identify precise active arrays spanning native Gateway auth
st.list_engines
json` extracting all active isolated Elastic indices bound per tenant. Identify bounded CRM records inside the Headless Swiftype Platform
st.post_search
json` firing raw queries into the specific Engine returning faceted JSON hierarchies. Perform structural extraction of properties driving active Account logic
st.post_suggest
json` bounding predictive keys and spelling tolerant matches decoupled from main indexing. Provision a highly-available JSON Payload generating hard Customer bindings
Example Prompts for Swiftype in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Swiftype immediately.
"List all my available Swiftype search engines, then run a search for 'documentation' on the most relevant one and show me the top 3 analytics clicks it generated last week."
"List all active engines in our Swiftype account."
"Run a test suggestion for 'passw' in the internal wiki engine."
Troubleshooting Swiftype MCP Server with LlamaIndex
Common issues when connecting Swiftype to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpSwiftype + LlamaIndex FAQ
Common questions about integrating Swiftype 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 Swiftype 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 Swiftype to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.