How to integrate Pinecone MCP with Pi

Connect Pi to Pinecone MCP. Query all vectors similar to user question, upsert document embeddings into a namespace, and more using natural language, with authentication handled for you.

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Pinecone

Api KeyOauth2

Pinecone is a fully managed vector database for high-performance AI memory and search. It lets you scale semantic search and retrieval without infrastructure overhead.

30 Tools

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We manage OAuth, API keys, token refresh, and scopes — you just build.

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Introduction

Pi is a minimal, self-extensible coding agent that lives in your terminal — one agent loop over Claude, GPT-5, Gemini, Grok, DeepSeek, and 20+ other providers, with maximum extension surface and minimum product opinion. Its core ships four tools (read, write, edit, bash) and self-extends at runtime through skills, extensions, and packages.

This guide explains the easiest and most robust way to connect your Pinecone account to Pi. You can do this through either Composio Connect CLI or Composio Connect MCP. Because Pi already runs shell commands as first-class tools and ships no built-in MCP, the CLI is the recommended path — it's faster to set up, needs no server config, and chains multi-step tasks more reliably. The MCP path is also fully supported through Pi's official pi-mcp-adapter extension.

What is Composio Connect?

Composio Connect is a consumer offering that lets anyone plug 1,000+ applications directly into their agent harness — including Pi. It can:

Search and load tools from relevant toolkits on-demand, reducing context usage.
Chain multiple tools to accomplish complex workflows via a remote workbench, without excessive back-and-forth with the LLM.
Manage app authentication end-to-end with zero manual overhead.

Connect Pinecone to Pi with Composio

Prerequisites: Install Pi

Pi needs Node.js 18+ (Node 22 recommended). Install the agent globally with npm:

bash

npm install -g --ignore-scripts @earendil-works/pi-coding-agent

On Linux or macOS you can use the installer script instead:

bash

curl -fsSL https://pi.dev/install.sh | sh

Then run pi in any project directory and authenticate your model provider — use /login inside Pi for subscription providers (Claude Pro/Max, ChatGPT, GitHub Copilot), or set an API key such as ANTHROPIC_API_KEY before starting. Confirm it's working:

bash

pi --version

Full first-run details are in the Pi Quickstart.

Option 1: Composio CLI (recommended)

Pi runs shell commands as first-class tools, so the Composio Universal CLI is the most natural fit — no MCP server to configure and reliable multi-step tool chaining. Install and authenticate:

bash

# Install the Composio CLI
curl -fsSL https://composio.dev/install | bash

# Log in to Composio
composio login

Connect to Pinecone

Ask Pi to connect to Pinecone, or simply request any Pinecone-related task. Under the hood Pi calls Composio commands like any other shell tool:

bash

composio search "what can I do with Pinecone?"
composio link pinecone

On the first Pinecone call, composio link pinecone opens an OAuth prompt so you can authorize access. After that, every Pinecone command works with your stored credentials automatically — just talk to Pi and it will search, execute, and chain Pinecone tools as needed.

Option 2: Composio MCP

Pi's core intentionally ships no built-in MCP, but the official pi-mcp-adapter extension adds full MCP support — exposing every server through a single lightweight proxy tool (~200 tokens) instead of loading hundreds of tool definitions into context.

1. Install the MCP adapter extension

bash

pi install npm:pi-mcp-adapter

Restart Pi after installation.

2. Add the Composio MCP server

Create (or edit) a .mcp.json file in your project root, or ~/.config/mcp/mcp.json for a user-global setup:

bash

{
  "mcpServers": {
    "composio": {
      "url": "https://connect.composio.dev/mcp"
    }
  }
}

The adapter connects lazily by default — the server won't start until Pi actually calls one of its tools, and cached metadata keeps search and describe working without a live connection.

3. Authenticate

Run /mcp-auth inside Pi to open the authentication modal and select composio from the list. Complete the sign-in in your browser, then on the consent screen click Allow access to authorize Composio. Once approved, the server shows as connected inside Pi:

Pi /mcp-auth modal listing the composio MCP server

Composio OAuth consent screen with the Allow access button

4. Done!

Confirm the server is live with /mcp to open the interactive panel, then ask Pi to connect to Pinecone or request any Pinecone-related task — it will prompt you to authorize Pinecone on first use.

What is the Pinecone MCP server, and what's possible with it?

The Pinecone MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Pinecone account. It provides structured and secure access so your agent can perform Pinecone operations on your behalf.

Way Forward

With Pinecone connected, Pi can now act on your behalf whenever you ask it to.

From here, you can extend Pi further:

Connect more apps: Calendar, Slack, Notion, Linear, and hundreds of others are available through the same Composio Connect setup. Each new integration compounds what Pi can do for you.
Build workflows across tools: Once multiple apps are connected, Pi can chain actions together — turn an email into a calendar invite, a Slack message into a Linear ticket, or a meeting note into a follow-up draft.
Lean into Pi's extension surface: Wrap common Pinecone flows as Pi skills or prompt templates so recurring tasks become one-line commands, and use directTools in the MCP adapter to promote your most-used Pinecone tools into Pi's tool list directly.

If you run into trouble or want to share what you've built, join the community or check out the Docs for deeper configuration options.

TOOLS

Supported Tools

Every Pinecone action and event your agent gets out of the box.

Cancel Bulk Import

Tool to cancel a bulk import operation in Pinecone.

Configure Index

Tool to configure an existing Pinecone index, including pod type, replicas, deletion protection, and tags.

Create Backup

Tool to create a backup of a Pinecone index for disaster recovery and version control.

Create Index

Tool to create a Pinecone index with specified configuration.

Create Index with Embedding Model

Tool to create a Pinecone index with integrated embedding model for automatic vectorization.

Create Index from Backup

Tool to create an index from a backup.

Create Namespace

Tool to create a namespace within a serverless Pinecone index.

Delete Index

Tool to permanently delete a Pinecone index.

Delete Namespace

Tool to permanently delete a namespace from a serverless index.

Describe Backup

Tool to retrieve detailed information about a specific backup.

Describe Bulk Import

Tool to describe a specific bulk import operation in Pinecone.

Describe Index Stats

Tool to get index statistics including vector count per namespace, dimensions, and fullness.

Describe Restore Job

Tool to get detailed information about a specific restore job in Pinecone.

Generate Embeddings

Tool to generate vector embeddings for input text using Pinecone's hosted embedding models.

Get Model Information

Tool to retrieve detailed information about a specific model hosted by Pinecone.

List Bulk Imports

Tool to list all recent and ongoing bulk import operations in Pinecone.

List Collections

Tool to list all collections in a Pinecone project (pod-based indexes only).

List Index Backups

Tool to list all backups for a specific Pinecone index.

List Indexes

Tool to list all indexes in a Pinecone project.

List Available Models

Tool to list all available embedding and reranking models hosted by Pinecone.

List Namespaces

Tool to list all namespaces in a serverless Pinecone index.

List Project Backups

Tool to list all backups for indexes in a Pinecone project.

List Restore Jobs

Tool to list all restore jobs for a project with pagination support.

List Vectors

Tool to list vector IDs in a Pinecone serverless index.

Query Vectors

Tool to perform semantic search within a Pinecone index using a query vector.

Rerank Documents

Tool to rerank documents by semantic relevance to a query.

Search Records in Namespace

Tool to search records within a Pinecone namespace using text, vector, or ID query.

Start Bulk Import

Tool to start an asynchronous bulk import of vectors from object storage (S3, GCS, or Azure Blob Storage) into a Pinecone index.

Update Vector

Tool to update a vector in Pinecone by ID.

Upsert Records to Namespace

Tool to upsert text records into a Pinecone namespace.

FRAMEWORKS

How to build Pinecone MCP Agent with another framework

ChatGPT Work

Use Pinecone MCP with ChatGPT Work

Antigravity

Use Pinecone MCP with Antigravity

OpenAI Agents SDK

Use Pinecone MCP with OpenAI Agents SDK

Claude Agent SDK

Use Pinecone MCP with Claude Agent SDK

Claude Code

Use Pinecone MCP with Claude Code

Claude Cowork

Use Pinecone MCP with Claude Cowork

Codex

Use Pinecone MCP with Codex

Grok Build

Use Pinecone MCP with Grok Build

Cursor

Use Pinecone MCP with Cursor

VS Code

Use Pinecone MCP with VS Code

OpenCode

Use Pinecone MCP with OpenCode

OpenClaw

Use Pinecone MCP with OpenClaw

Hermes

Use Pinecone MCP with Hermes

Google ADK

Use Pinecone MCP with Google ADK

LangChain

Use Pinecone MCP with LangChain

Vercel AI SDK

Use Pinecone MCP with Vercel AI SDK

Mastra AI

Use Pinecone MCP with Mastra AI

LlamaIndex

Use Pinecone MCP with LlamaIndex

CrewAI

Use Pinecone MCP with CrewAI

Pydantic AI

Use Pinecone MCP with Pydantic AI

AutoGen

Use Pinecone MCP with AutoGen

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FAQ

Frequently asked questions

With a standalone Pinecone MCP server, the agents and LLMs can only access a fixed set of Pinecone tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Pinecone and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Pi fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Pinecone tools.

Yes, absolutely. You can configure which Pinecone scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Pinecone data and credentials are handled as safely as possible.

Start with Pinecone.It takes 30 seconds.

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How to integrate Pinecone MCP with Pi

Connect Pinecone without auth hassles

Introduction

Also integrate Pinecone with

What is Composio Connect?

Connect Pinecone to Pi with Composio

Prerequisites: Install Pi

Option 1: Composio CLI (recommended)

Connect to Pinecone

Option 2: Composio MCP

1. Install the MCP adapter extension

2. Add the Composio MCP server

3. Authenticate

4. Done!

What is the Pinecone MCP server, and what's possible with it?

Way Forward

Supported Tools

How to build Pinecone MCP Agent with another framework

ChatGPT Work

Antigravity

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

Grok Build

Cursor

VS Code

OpenCode

OpenClaw

Hermes

Google ADK

LangChain

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

Pydantic AI

AutoGen

Explore Other Toolkits

Supabase

Composio

Codeinterpreter

GitHub

Frequently asked questions

What are the differences in Tool Router MCP and Pinecone MCP?+

Can I use Tool Router MCP with Pi?+

Can I manage the permissions and scopes for Pinecone while using Tool Router?+

How safe is my data with Composio Tool Router?+

Start with Pinecone.It takes 30 seconds.