Pinecone Integration for AI Agents

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with Pinecone MCP or direct API to index vectors, run similarity searches, manage namespaces, and retrieve embeddings through natural language.
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Enter a prompt below to test the integration in our Tool Router playground. You'll be redirected to sign in and try it live.

Supported Tools

Tools
Cancel Bulk ImportTool to cancel a bulk import operation in Pinecone.
Configure IndexTool to configure an existing Pinecone index, including pod type, replicas, deletion protection, and tags.
Create BackupTool to create a backup of a Pinecone index for disaster recovery and version control.
Create IndexTool to create a Pinecone index with specified configuration.
Create Index with Embedding ModelTool to create a Pinecone index with integrated embedding model for automatic vectorization.
Create Index from BackupTool to create an index from a backup.
Create NamespaceTool to create a namespace within a serverless Pinecone index.
Delete IndexTool to permanently delete a Pinecone index.
Delete NamespaceTool to permanently delete a namespace from a serverless index.
Describe BackupTool to retrieve detailed information about a specific backup.
Describe Bulk ImportTool to describe a specific bulk import operation in Pinecone.
Describe Index StatsTool to get index statistics including vector count per namespace, dimensions, and fullness.
Describe Restore JobTool to get detailed information about a specific restore job in Pinecone.
Generate EmbeddingsTool to generate vector embeddings for input text using Pinecone's hosted embedding models.
Get Model InformationTool to retrieve detailed information about a specific model hosted by Pinecone.
List Bulk ImportsTool to list all recent and ongoing bulk import operations in Pinecone.
List CollectionsTool to list all collections in a Pinecone project (pod-based indexes only).
List Index BackupsTool to list all backups for a specific Pinecone index.
List IndexesTool to list all indexes in a Pinecone project.
List Available ModelsTool to list all available embedding and reranking models hosted by Pinecone.
List NamespacesTool to list all namespaces in a serverless Pinecone index.
List Project BackupsTool to list all backups for indexes in a Pinecone project.
List Restore JobsTool to list all restore jobs for a project with pagination support.
List VectorsTool to list vector IDs in a Pinecone serverless index.
Query VectorsTool to perform semantic search within a Pinecone index using a query vector.
Rerank DocumentsTool to rerank documents by semantic relevance to a query.
Search Records in NamespaceTool to search records within a Pinecone namespace using text, vector, or ID query.
Start Bulk ImportTool to start an asynchronous bulk import of vectors from object storage (S3, GCS, or Azure Blob Storage) into a Pinecone index.
Update VectorTool to update a vector in Pinecone by ID.
Upsert Records to NamespaceTool to upsert text records into a Pinecone namespace.
Python
TypeScript

Install Composio

python
pip install composio claude-agent-sdk
Install the Composio SDK for Python or TypeScript

Initialize Client and Create Tool Router Session

python
from composio import Composio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions

composio = Composio(api_key='your-composio-api-key')
session = composio.create(user_id='your-user-id')
url = session.mcp.url
Import and initialize the Composio client, then create a Tool Router session for Pinecone

Connect to AI Agent

python
import asyncio

options = ClaudeAgentOptions(
    permission_mode='bypassPermissions',
    mcp_servers={
        'tool_router': {
            'type': 'http',
            'url': url,
            'headers': {
                'x-api-key': 'your-composio-api-key'
            }
        }
    },
    system_prompt='You are a helpful assistant with access to Pinecone tools.',
    max_turns=10
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query('Upsert new document vectors to the "research_papers" namespace.')
        async for message in client.receive_response():
            if hasattr(message, 'content'):
                for block in message.content:
                    if hasattr(block, 'text'):
                        print(block.text)

asyncio.run(main())
Use the MCP server with your AI agent (Anthropic Claude or Mastra)

Why Use Composio?

AI Native Pinecone Integration

  • Supports both Pinecone MCP and direct API based integrations
  • Structured, LLM-friendly schemas for reliable tool execution
  • Rich coverage for reading, writing, and querying your Pinecone data

Managed Auth

  • Built-in OAuth handling with automatic token refresh and rotation
  • Central place to manage, scope, and revoke Pinecone access
  • Per user and per environment credentials instead of hard-coded keys

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

Enterprise Grade Security

  • Fine-grained RBAC so you control which agents and users can access Pinecone
  • Scoped, least privilege access to Pinecone resources
  • Full audit trail of agent actions to support review and compliance

Use Pinecone with any AI Agent Framework

Choose a Framework you want to connect Pinecone with

Frequently Asked Questions

Do I need my own developer credentials to use Pinecone with Composio?

Yes, Pinecone 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.

Is Composio secure?

Composio is SOC 2 and ISO 27001 compliant with all data encrypted in transit and at rest. Learn more.

What if the API changes?

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

Used by agents from

Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.

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