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 LangChain 10 tools — connect in under 2 minutes

Name: Sanity
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Sanity through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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 langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "sanity": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Sanity, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

LangChain's ecosystem of 500+ components combines seamlessly with Sanity through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

Follow these steps to integrate the Sanity MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from Sanity via MCP

Why Use LangChain with the Sanity MCP Server

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

The largest ecosystem of integrations, chains, and agents. combine Sanity MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Sanity queries for multi-turn workflows

Sanity + LangChain Use Cases

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

RAG with live data: combine Sanity tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Sanity, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Sanity tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Sanity tool call, measure latency, and optimize your agent's performance

Sanity MCP Tools for LangChain (10)

These 10 tools become available when you connect Sanity to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Sanity + LangChain FAQ

Common questions about integrating Sanity MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.