pinecone-cli
Pinecone CLI (pc)
Manage Pinecone from the terminal. The CLI is especially valuable for vector operations across all index types — something the MCP currently can't do.
CLI vs MCP
| CLI | MCP | |
|---|---|---|
| Index types | All (standard, integrated, sparse) | Integrated only |
| Vector ops (upsert, query, fetch, update, delete) | ✅ | ❌ |
| Text search on integrated indexes | ✅ | ✅ |
| Backups, namespaces, org/project mgmt | ✅ | ❌ |
| CI/CD / scripting | ✅ | ❌ |
Setup
Install (macOS)
brew tap pinecone-io/tap
brew install pinecone-io/tap/pinecone
Other platforms (Linux, Windows) — download from GitHub Releases.
Authenticate
# Interactive (recommended for local dev)
pc login
pc target -o "my-org" -p "my-project"
# Service account (recommended for CI/CD)
pc auth configure --client-id "$PINECONE_CLIENT_ID" --client-secret "$PINECONE_CLIENT_SECRET"
# API key (quick testing)
pc config set-api-key $PINECONE_API_KEY
Check status: pc auth status · pc target --show
Note for agent sessions: If you need to run
pc logininside an agent loop, the browser auth link may not surface correctly. It's best to authenticate before starting an agent session. Runpc loginin your terminal directly, then invoke the agent once you're authenticated.
Authenticating the CLI does not set PINECONE_API_KEY
pc login authenticates the CLI tool itself — it does not set PINECONE_API_KEY in your environment. Python scripts, Node.js SDKs, and other tools that use the Pinecone SDK need PINECONE_API_KEY set separately.
Use the CLI to create a key and export it in one step:
KEY=$(pc api-key create --name agent-sdk-key --json | jq -r '.value')
export PINECONE_API_KEY="$KEY"
Without jq: run pc api-key create --name agent-sdk-key --json and copy the "value" field manually.
Common Commands
| Task | Command |
|---|---|
| List indexes | pc index list |
| Create serverless index | pc index create -n my-index -d 1536 -m cosine -c aws -r us-east-1 |
| Index stats | pc index stats -n my-index |
| Upload vectors from file | pc index vector upsert -n my-index --file ./vectors.json |
| Query by vector | pc index vector query -n my-index --vector '[0.1, ...]' -k 10 --include-metadata |
| Query by vector ID | pc index vector query -n my-index --id "doc-123" -k 10 |
| Fetch vectors by ID | pc index vector fetch -n my-index --ids '["vec1","vec2"]' |
| List vector IDs | pc index vector list -n my-index |
| Delete vectors by filter | pc index vector delete -n my-index --filter '{"genre":"classical"}' |
| List namespaces | pc index namespace list -n my-index |
| Create backup | pc backup create -i my-index -n "my-backup" |
| JSON output (for scripting) | Add -j to any command |
Interesting Things You Can Do
Query with custom vectors (not just text)
Unlike the MCP, the CLI lets you query any index with raw vector values — useful when you generate embeddings externally (OpenAI, HuggingFace, etc.):
pc index vector query -n my-index \
--vector '[0.1, 0.2, ..., 0.9]' \
--filter '{"source":{"$eq":"docs"}}' \
-k 20 --include-metadata
Pipe embeddings directly into queries
jq -c '.embedding' doc.json | pc index vector query -n my-index --vector - -k 10
Bulk metadata update with preview
# Preview first
pc index vector update -n my-index \
--filter '{"env":{"$eq":"staging"}}' \
--metadata '{"env":"production"}' \
--dry-run
# Apply
pc index vector update -n my-index \
--filter '{"env":{"$eq":"staging"}}' \
--metadata '{"env":"production"}'
Backup and restore
# Snapshot before a migration
pc backup create -i my-index -n "pre-migration"
# Restore to a new index if something goes wrong
pc backup restore -i <backup-uuid> -n my-index-restored
Automate in CI/CD
export PINECONE_CLIENT_ID="..."
export PINECONE_CLIENT_SECRET="..."
pc auth configure --client-id "$PINECONE_CLIENT_ID" --client-secret "$PINECONE_CLIENT_SECRET"
pc index vector upsert -n my-index --file ./vectors.jsonl --batch-size 1000
Script against JSON output
# Get all index names as a list
pc index list -j | jq -r '.[] | .name'
# Check if an index exists before creating
if ! pc index describe -n my-index -j 2>/dev/null | jq -e '.name' > /dev/null; then
pc index create -n my-index -d 1536 -m cosine -c aws -r us-east-1
fi
Reference Files
- Full command reference — all commands with flags and examples
- Troubleshooting & best practices
Documentation
More from pinecone-io/skills
pinecone-docs
Curated documentation reference for developers building with Pinecone. Contains links to official docs organized by topic and data format references. Use when writing Pinecone code, looking up API parameters, or needing the correct format for vectors or records.
61pinecone-help
Overview of all available Pinecone skills and what a user needs to get started. Invoke when a user asks what skills are available, how to get started with Pinecone, or what they need to set up before using any Pinecone skill.
53pinecone-assistant
Create, manage, and chat with Pinecone Assistants for document Q&A with citations. Handles all assistant operations - create, upload, sync, chat, context retrieval, and list. Recognizes natural language like "create an assistant from my docs", "ask my assistant about X", or "upload my docs to Pinecone".
49pinecone-query
Query integrated indexes using text with Pinecone MCP. IMPORTANT - This skill ONLY works with integrated indexes (indexes with built-in Pinecone embedding models like multilingual-e5-large). For standard indexes or advanced vector operations, use the CLI skill instead. Requires PINECONE_API_KEY environment variable and Pinecone MCP server to be configured.
47pinecone-mcp
Reference for the Pinecone MCP server tools. Documents all available tools - list-indexes, describe-index, describe-index-stats, create-index-for-model, upsert-records, search-records, cascading-search, and rerank-documents. Use when an agent needs to understand what Pinecone MCP tools are available, how to use them, or what parameters they accept.
43pinecone-quickstart
Interactive Pinecone quickstart for new developers. Choose between two paths - Database (create an integrated index, upsert data, and query using Pinecone MCP + Python) or Assistant (create a Pinecone Assistant for document Q&A). Use when a user wants to get started with Pinecone for the first time or wants a guided tour of Pinecone's tools.
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