# Weaviate MCP

```json
{
  "name": "Weaviate MCP",
  "slug": "weaviate_mcp",
  "url": "https://composio.dev/toolkits/weaviate_mcp",
  "markdown_url": "https://composio.dev/toolkits/weaviate_mcp.md",
  "logo_url": "https://logos.composio.dev/api/weaviate_mcp",
  "categories": [
    "ai & machine learning",
    "data & analytics"
  ],
  "is_composio_managed": false,
  "updated_at": "2026-10-21T05:34:00.503Z"
}
```

![Weaviate MCP logo](https://logos.composio.dev/api/weaviate_mcp)

## Description

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with Weaviate MCP or direct API to search collections, answer questions, retrieve relevant objects, and explore vector data through natural language.

## Summary

Weaviate MCP is a provider-hosted Query Agent for searching Weaviate Cloud collections.
It turns natural-language questions into AI-powered collection searches.

## Categories

- ai & machine learning
- data & analytics

## Toolkit Details

- Tools: 2

## Images

- Logo: https://logos.composio.dev/api/weaviate_mcp

## Authentication

- **Api Key**
  - Type: `api_key`
  - Description: Api Key authentication for Weaviate MCP.
  - Setup:
    - Configure Api Key credentials for Weaviate MCP.
    - Use the credentials when creating an auth config in Composio.

## Suggested Prompts

- Search Weaviate collections for API errors
- Find customer feedback about onboarding issues
- Compare research papers on vector databases

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `WEAVIATE_MCP_QUERY_AGENT_ASK` | Query agent ask | Ask Mode transforms your query into actionable searches or aggregations, and then provides a final answer to the question. For example, you could ask: "How many orders related to books were placed last week?" And the agent will filter for orders, perform semantic search for books and sort or filter for timestamps from the last week. Then, the agent will provide a response, answering this question exactly based on the data retrieved. The result always carries final_answer. When result_evaluation is 'llm', it additionally carries is_partial_answer (whether information the query asked for is missing from the answer), missing_information (what exactly could not be found in the data), and sources (the retrieved objects the answer actually drew on). Queries the collections named in the request within your connected Weaviate Cloud cluster. Use collection names from your own cluster; access follows the connected API key permissions. |
| `WEAVIATE_MCP_QUERY_AGENT_SEARCH` | Query agent search | Search Mode combines AI-powered semantic search with structured filtering and returns the matching Weaviate objects directly. For example, you could ask: "Find me some vintage shoes under $70" And the agent will perform semantic search for vintage shoes, apply a filter for price < 70, and return the matching objects from your collections, ready for you to render or post-process. You could also ask: "Something comfortable to wear on a long flight" And the agent will use AI-powered search to find relevant objects, even when terms like comfortable or long flight never appear in your data. Under the hood, Search Mode does more than embed your query as-is. The agent writes one or more optimized semantic and structured queries, executes them against your collections, and reranks the retrieved objects by how well each one matches your original request. The result's `results` field lists the matching objects in rank order (best match first), each as a dict of property names to values. Queries the collections named in the request within your connected Weaviate Cloud cluster. Use collection names from your own cluster; access follows the connected API key permissions. |

## Supported Triggers

None listed.

## Installation and MCP Setup

### Path 1: SDK Installation

#### Path 1, Step 1: Install Composio

Install the Composio SDK, the OpenAI provider, and the OpenAI SDK
```python
pip install composio composio_openai openai
```

```typescript
npm install @composio/core @composio/openai openai
```

#### Path 1, Step 2: Create a Composio session

Initialize Composio with the OpenAI Responses provider and create a session scoped to Weaviate MCP
```python
import json
from openai import OpenAI
from composio import Composio
from composio_openai import OpenAIResponsesProvider

composio = Composio(provider=OpenAIResponsesProvider())
client = OpenAI()

session = composio.create(user_id="your-user-id", toolkits=["weaviate_mcp"])
tools = session.tools()
```

```typescript
import OpenAI from "openai";
import { Composio } from "@composio/core";
import { OpenAIResponsesProvider } from "@composio/openai";

const composio = new Composio({ provider: new OpenAIResponsesProvider() });
const client = new OpenAI();

const session = await composio.create("your-user-id", { toolkits: ["weaviate_mcp"] });
const tools = await session.tools();
```

#### Path 1, Step 3: Run Weaviate MCP tools with your agent

Send a request, execute the Weaviate MCP tool calls through the session, and print the final answer
```python
response = client.responses.create(
    model="gpt-5.6-sol",
    tools=tools,
    input=[{"role": "user", "content": "Search my Weaviate Cloud collections for documents about reducing vector search latency and summarize the three most relevant findings."}],
)

while True:
    tool_calls = [o for o in response.output if o.type == "function_call"]
    if not tool_calls:
        break
    results = composio.provider.handle_tool_calls(response=response, session=session)
    response = client.responses.create(
        model="gpt-5.6-sol",
        tools=tools,
        previous_response_id=response.id,
        input=[
            {"type": "function_call_output", "call_id": call.call_id, "output": json.dumps(results[i])}
            for i, call in enumerate(tool_calls)
        ],
    )

print(response.output_text)
```

```typescript
let response = await client.responses.create({
  model: "gpt-5.6-sol",
  tools,
  input: [{ role: "user", content: "Search my Weaviate Cloud collections for documents about reducing vector search latency and summarize the three most relevant findings." }],
});

while (response.output.some((o) => o.type === "function_call")) {
  const outputs = await composio.provider.handleToolCalls(session, response.output);
  response = await client.responses.create({
    model: "gpt-5.6-sol",
    tools,
    previous_response_id: response.id,
    input: outputs,
  });
}

console.log(response.output_text);
```

### Path 2: MCP Server Setup

#### Path 2, Step 1: Install Composio

Install the Composio SDK and your agent framework
```python
pip install composio claude-agent-sdk
```

```typescript
npm install @composio/core ai @ai-sdk/mcp @ai-sdk/openai
```

#### Path 2, Step 2: Create a session with MCP enabled

Create a session scoped to Weaviate MCP and read its MCP URL and headers
```python
from composio import Composio

composio = Composio()
session = composio.create(user_id="your-user-id", toolkits=["weaviate_mcp"], mcp=True)
```

```typescript
import { Composio } from "@composio/core";

const composio = new Composio();
const { mcp } = await composio.create("your-user-id", {
  toolkits: ["weaviate_mcp"],
  mcp: true,
});
```

#### Path 2, Step 3: Connect your agent to the MCP server

Pass the session's MCP URL and headers to your agent and run a Weaviate MCP request
```python
import asyncio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions, AssistantMessage, TextBlock

options = ClaudeAgentOptions(
    mcp_servers={
        "composio": {
            "type": "http",
            "url": session.mcp.url,
            "headers": session.mcp.headers,
        }
    },
    system_prompt="You are a helpful assistant with access to Weaviate MCP tools.",
    tools=[],
    allowed_tools=["mcp__composio__*"],
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query("Search my Weaviate Cloud collections for documents about reducing vector search latency and summarize the three most relevant findings.")
        async for message in client.receive_response():
            if isinstance(message, AssistantMessage):
                for block in message.content:
                    if isinstance(block, TextBlock):
                        print(block.text)

asyncio.run(main())
```

```typescript
import { createMCPClient } from "@ai-sdk/mcp";
import { openai } from "@ai-sdk/openai";
import { generateText, stepCountIs } from "ai";

const client = await createMCPClient({
  transport: { type: "http", url: mcp.url, headers: mcp.headers },
});

const { text } = await generateText({
  model: openai("gpt-5.6-sol"),
  tools: await client.tools(),
  prompt: "Search my Weaviate Cloud collections for documents about reducing vector search latency and summarize the three most relevant findings.",
  stopWhen: stepCountIs(10),
});

console.log(text);
await client.close();
```

## Why Use Composio?

### 1. AI Native Weaviate MCP Integration

- Supports both Weaviate MCP and direct API-based integrations
- Structured, LLM-friendly schemas for reliable collection queries
- Rich coverage for searching and retrieving data from Weaviate Cloud

### 2. Secure API Key Handling

- Connect Weaviate MCP with your own API key credentials
- Central place to manage, scope, and revoke Weaviate access
- Per-user and per-environment credentials instead of hard-coded keys

### 3. Agent Optimized Design

- Tools are tuned using real error and success rates to improve reliability over time
- Comprehensive execution logs so you always know what ran, when, and on whose behalf

### 4. Enterprise Grade Security

- Fine-grained RBAC so you control which agents and users can access Weaviate MCP
- Scoped, least-privilege access to Weaviate Cloud collections
- Full audit trail of agent actions to support review and compliance

## Use Weaviate MCP with any AI Agent Framework

Choose a framework you want to connect Weaviate MCP with:

- [ChatGPT](https://composio.dev/toolkits/weaviate_mcp/framework/chatgpt)
- [Claude Cowork](https://composio.dev/toolkits/weaviate_mcp/framework/claude-cowork)
- [Hermes](https://composio.dev/toolkits/weaviate_mcp/framework/hermes-agent)
- [Atomic Agent](https://composio.dev/toolkits/weaviate_mcp/framework/atomic-agent)

## Related Toolkits

- [Composio](https://composio.dev/toolkits/composio) - Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed.
- [Firecrawl](https://composio.dev/toolkits/firecrawl) - Firecrawl automates large-scale web crawling and data extraction. It helps organizations efficiently gather, index, and analyze content from online sources.
- [Composio search](https://composio.dev/toolkits/composio_search) - Composio search is a unified web search toolkit spanning travel, e-commerce, news, financial markets, images, and more. It lets you and your apps tap into up-to-date web data from a single, easy-to-integrate service.
- [Tavily](https://composio.dev/toolkits/tavily) - Tavily offers powerful search and data retrieval from documents, databases, and the web. It helps teams locate and filter information instantly, saving hours on research.
- [Exa](https://composio.dev/toolkits/exa) - Exa is a data extraction and search platform for gathering and analyzing information from websites, APIs, or databases. It helps teams quickly surface insights and automate data-driven workflows.
- [Serpapi](https://composio.dev/toolkits/serpapi) - SerpApi is a real-time API for structured search engine results. It lets you automate SERP data collection, parsing, and analysis for SEO and research.
- [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. It's the go-to tool for calculations, reporting, and flexible data management.
- [Perplexityai](https://composio.dev/toolkits/perplexityai) - Perplexityai delivers natural, conversational AI models for generating human-like text. Instantly get context-aware, high-quality responses for chat, search, or complex workflows.
- [Peopledatalabs](https://composio.dev/toolkits/peopledatalabs) - Peopledatalabs delivers B2B data enrichment and identity resolution APIs. Supercharge your apps with accurate, up-to-date business and contact data.
- [Snowflake](https://composio.dev/toolkits/snowflake) - Snowflake is a cloud data warehouse built for elastic scaling, secure data sharing, and fast SQL analytics across major clouds.
- [Browser tool](https://composio.dev/toolkits/browser_tool) - Browser tool is a virtual browser integration that lets AI agents interact with the web programmatically. It enables automated browsing, scraping, and action-taking from any AI workflow.
- [Posthog](https://composio.dev/toolkits/posthog) - PostHog is an open-source analytics platform for tracking user interactions and product metrics. It helps teams refine features, analyze funnels, and reduce churn with actionable insights.
- [21risk](https://composio.dev/toolkits/_21risk) - 21RISK is a web app built for easy checklist, audit, and compliance management. It streamlines risk processes so teams can focus on what matters.
- [Abstract](https://composio.dev/toolkits/abstract) - Abstract provides a suite of APIs for automating data validation and enrichment tasks. It helps developers streamline workflows and ensure data quality with minimal effort.
- [AccuWeather](https://composio.dev/toolkits/accu_weather) - AccuWeather is a global weather service providing current conditions, forecasts, MinuteCast precipitation, alerts, and lightning data. Use it for fast, localized forecasts and real-time weather alerts.
- [Adafruit IO](https://composio.dev/toolkits/adafruit_io) - Adafruit IO is Adafruit's cloud platform for connected device and IoT project data. It helps you store, visualize, and act on sensor feeds without running your own backend.
- [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time.
- [Agentql](https://composio.dev/toolkits/agentql) - Agentql is a toolkit that connects AI agents to the web using a specialized query language. It enables structured web interaction and data extraction for smarter automations.
- [Agenty](https://composio.dev/toolkits/agenty) - Agenty is a web scraping and automation platform for extracting data and automating browser tasks—no coding needed. It streamlines data collection, monitoring, and repetitive online actions.
- [Ahrefs MCP](https://composio.dev/toolkits/ahrefs_mcp) - Ahrefs MCP is Ahrefs' hosted MCP server for SEO data and insights. Use it to access backlinks, organic metrics, keyword research, and competitor analysis.

## Frequently Asked Questions

### Do I need my own developer credentials to use Weaviate MCP with Composio?

Yes, Weaviate MCP requires you to configure your own API key credentials. Once set up, Composio handles secure credential storage and API request handling for you.

### Can I use multiple toolkits together?

Yes! Composio's Tool Router enables agents to use multiple toolkits. [Learn more](https://docs.composio.dev/tool-router/overview).

### Is Composio secure?

Composio is SOC 2 and ISO 27001 compliant with all data encrypted in transit and at rest. [Learn more](https://trust.composio.dev).

### What if the API changes?

Composio maintains and updates all toolkit integrations automatically, so your agents always work with the latest API versions.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)