Pinecone MCP Server for Mastra AI 7 tools — connect in under 2 minutes
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Pinecone through Vinkius and Mastra agents discover all tools automatically. type-safe, streaming-ready, and deployable anywhere Node.js runs.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";
async function main() {
// Your Vinkius token. get it at cloud.vinkius.com
const mcpClient = await createMCPClient({
servers: {
"pinecone": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "Pinecone Agent",
instructions:
"You help users interact with Pinecone " +
"using 7 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with Pinecone?"
);
console.log(result.text);
}
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 Pinecone MCP Server
Connect your Pinecone knowledge graph environment straight into your AI agent's logic. Give your preferred Large Language Model the keys to fetch, query, and modify vector spaces via natural language context without leaving the chat interface.
Mastra's agent abstraction provides a clean separation between LLM logic and Pinecone tool infrastructure. Connect 7 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.
What you can do
- Index Hierarchy — Retrieve structural blueprints instantly using
list_indexesand fetch intricate topology parameters utilizingdescribe_index. - Semantic Harvesting — Pass pure array values to execute blazing-fast retrieval with
query_vectors, or pinpoint specific embeddings natively employingfetch_vectors. - Space Archiving — Monitor grouped snapshot arrays leveraging
list_collectionsand perform surgical cleanups executingdelete_vectorsaccurately. - Performance Auditing — Ask the model to pull real-time health checks calling
get_index_statsto reveal vector capacity limits across pods.
The Pinecone MCP Server exposes 7 tools through the Vinkius. Connect it to Mastra AI 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 Pinecone to Mastra AI via MCP
Follow these steps to integrate the Pinecone MCP Server with Mastra AI.
Install dependencies
Run npm install @mastra/core @mastra/mcp @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.ts and run with npx tsx agent.ts
Explore tools
Mastra discovers 7 tools from Pinecone via MCP
Why Use Mastra AI with the Pinecone MCP Server
Mastra AI provides unique advantages when paired with Pinecone through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add Pinecone without touching business code
Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
TypeScript-native: full type inference for every Pinecone tool response with IDE autocomplete and compile-time checks
One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure
Pinecone + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the Pinecone MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query Pinecone, process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed Pinecone as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query Pinecone on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using Pinecone tools alongside other MCP servers
Pinecone MCP Tools for Mastra AI (7)
These 7 tools become available when you connect Pinecone to Mastra AI via MCP:
delete_vectors
Delete vectors from an index
describe_index
Get configuration details for an index
fetch_vectors
Fetch specific vectors by their IDs
get_index_stats
Get usage statistics for an index
list_collections
List all index collections
list_indexes
List all Pinecone indexes
query_vectors
Returns the most similar vectors and their metadata. Search for similar vectors
Example Prompts for Pinecone in Mastra AI
Ready-to-use prompts you can give your Mastra AI agent to start working with Pinecone immediately.
"Check the vector count stats for the index named `document-embeddings`."
"Delete all vectors belonging to the user ID 'auth-abc123' namespace."
"List all existing collections created in my Pinecone environment."
Troubleshooting Pinecone MCP Server with Mastra AI
Common issues when connecting Pinecone to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpPinecone + Mastra AI FAQ
Common questions about integrating Pinecone MCP Server with Mastra AI.
How does Mastra AI connect to MCP servers?
MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.Can Mastra agents use tools from multiple servers?
Does Mastra support workflow orchestration?
Connect Pinecone 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 Pinecone to Mastra AI
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.