Can my AI agent write complex GROQ queries for me?

Yes. If you know what data you want but aren't totally familiar with GROQ syntax, you can simply ask your agent: 'Write and execute a GROQ query to find all author documents where the name starts with John and return just their ID and bio.' The agent will draft the query, execute it via the `run_groq_query` tool, and return the filtered JSON.

How do I perform a bulk update on my documents?

You can ask your agent to first fetch the documents (e.g., 'List all posts missing a category'), calculate the changes needed, and then use the `run_raw_mutation` tool or `patch_cms_document` iteratively to apply the updates. This acts as a conversational migration script, updating dozens of documents safely and quickly.

Can the agent check if media assets are missing from my posts?

Yes. The agent can use the document querying tools combined with `list_media_assets` to analyze your content. For instance, you can ask it to generate a report of all products that do not have an associated image reference, giving you an exact list of items to fix in the Studio.

Sanity MCP Server for LlamaIndex 10 tools — connect in under 2 minutes

Name: Sanity
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

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 Sanity. "
            "You have 10 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Sanity?"
    )
    print(response)

asyncio.run(main())

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* 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 Sanity MCP Server

Connect your Sanity project to any AI agent and take full control of your Content Lake through natural conversation.

LlamaIndex agents combine Sanity 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

GROQ Queries — Execute powerful Graph-Relational Object Queries to fetch exactly the content you need
Document Management — Create, read, update, patch, and delete documents of any schema type
Schema Insights — List unique schema types and count entity nodes dynamically
Media Assets — Browse and manage images and file assets uploaded to your project
Bulk Operations — Run raw Sanity mutations for complex, multi-document transactions

The Sanity 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 Sanity to LlamaIndex via MCP

Follow these steps to integrate the Sanity 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 Sanity

Why Use LlamaIndex with the Sanity MCP Server

LlamaIndex provides unique advantages when paired with Sanity through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Sanity tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Sanity tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Sanity, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Sanity tools were called, what data was returned, and how it influenced the final answer

Sanity + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Sanity MCP Server delivers measurable value.

Hybrid search: combine Sanity real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Sanity 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 Sanity for fresh data

Analytical workflows: chain Sanity queries with LlamaIndex's data connectors to build multi-source analytical reports

Sanity MCP Tools for LlamaIndex (10)

These 10 tools become available when you connect Sanity to LlamaIndex via MCP:

count_entity_nodes

Counts the number of documents of a specific type

create_cms_document

Specify the type and provide attributes as a JSON object. Creates a new document in the CMS

get_document_details

Retrieves full details for a specific document by ID

list_media_assets

Lists all image and file assets uploaded to Sanity

list_typed_documents

g., "post", "author"). Lists all documents of a specific type

list_unique_schema_types

Retrieves a list of all unique document types present in the dataset

patch_cms_document

Provide a JSON object of fields to set. Updates specific fields of an existing document

run_groq_query

Executes a GROQ (Graph-Relational Object Queries) query

run_raw_mutation

Provide a JSON array of mutation objects. Executes a raw Sanity mutation

wipe_cms_document

This action is irreversible. Permanently deletes a document from the CMS

Example Prompts for Sanity in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Sanity immediately.

"List all unique schema types in my dataset."

"Write a GROQ query to find the 3 most recently updated authors."

"Update the post with ID 'drafts.1234' and set its published state to true."

Troubleshooting Sanity MCP Server with LlamaIndex

Common issues when connecting Sanity to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Sanity + LlamaIndex FAQ

Common questions about integrating Sanity 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 Sanity tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.