assistant
Create, manage, and chat with Pinecone Assistants for document Q&A with citations. Handles all assistant operations - create,…
Guide for using the Pinecone CLI (pc) to manage Pinecone resources from the terminal. The CLI supports ALL index types (standard, integrated, sparse) and all vector operations — unlike the MCP which only supports integrated indexes. Use for batch operations, vector management,
Claude Code
$ npx -y skills add pinecone-io/pinecone-claude-code-plugin --skill cli --agent claude-code
Codex
$ npx skills add pinecone-io/pinecone-claude-code-plugin --skill cli -a codex -y
Cursor
$ npx skills add pinecone-io/pinecone-claude-code-plugin --skill cli -a cursor -y
Gemini CLI
$ npx skills add pinecone-io/pinecone-claude-code-plugin --skill cli -a gemini-cli -y
GitHub Copilot
$ npx skills add pinecone-io/pinecone-claude-code-plugin --skill cli -a github-copilot -y
OpenCode
$ npx skills add pinecone-io/pinecone-claude-code-plugin --skill cli -a opencode -y
Windsurf
$ npx skills add pinecone-io/pinecone-claude-code-plugin --skill cli -a windsurf -y
name: pinecone:cli description: Guide for using the Pinecone CLI (pc) to manage Pinecone resources from the terminal. The CLI supports ALL index types (standard, integrated, sparse) and all vector operations — unlike the MCP which only supports integrated indexes. Use for batch operations, vector management, backups, namespaces, CI/CD automation, and full control over Pinecone resources. argument-hint: install | auth | index [op] | vector [op] | backup | namespace allowed-tools: Bash, Read
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 | 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 | ✅ | ❌ |
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brew tap pinecone-io/tap brew install pinecone-io/tap/pinecone
Other platforms (Linux, Windows) — download from [GitHub Releases](https://github.com/pinecone-io/cli/releases).
# 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 $PINECONE_API_KEY
Check status: `pc auth status` · `pc target --show`
> **Note for agent sessions**: If you need to run `pc login` inside an agent loop, the browser auth link may not surface correctly. It's best to authenticate **before** starting an agent session. Run `pc login` in your terminal directly, then invoke the agent once you're authenticated.
`pc login` authenticates the CLI tool itself — it does **not** set `PINECONE_API_KEY` in your environment. Python scripts, Node.js SDKs, and other tools that use the Pinecone SDK need `PINECONE_API_KEY` set separately.
Use the CLI to create a key and export it in one step:
KEY=$(pc api-key create --name agent-sdk-key --json | jq -r '.value') export PINECONE_API_KEY="$KEY"
Without `jq`: run `pc api-key create --name agent-sdk-key --json` and copy the `"value"` field manually.
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| Task | Command | |---|---| | List indexes | `pc index list` | | Create serverless index | `pc index create -n my-index -d 1536 -m cosine -c aws -r us-east-1` | | Index stats | `pc index stats -n my-index` | | Upload vectors from file | `pc index vector upsert -n my-index --file ./vectors.json` | | Query by vector | `pc index vector query -n my-index --vector '[0.1, ...]' -k 10 --include-metadata` | | Query by vector ID | `pc index vector query -n my-index --id "doc-123" -k 10` | | Fetch vectors by ID | `pc index vector fetch -n my-index --ids '["vec1","vec2"]'` | | List vector IDs | `pc index vector list -n my-index` | | Delete vectors by filter | `pc index vector delete -n my-index --filter '{"genre":"classical"}'` | | List namespaces | `pc index namespace list -n my-index` | | Create backup | `pc backup create -i my-index -n "my-backup"` | | JSON output (for scripting) | Add `-j` to any command |
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Unlike the MCP, the CLI lets you query any index with raw vector values — useful when you generate embeddings externally (OpenAI, HuggingFace, etc.):
pc index vector query -n my-index \
--vector '[0.1, 0.2, ..., 0.9]' \
--filter '{"source":{"$eq":"docs"}}' \
-k 20 --include-metadatajq -c '.embedding' doc.json | pc index vector query -n my-index --vector - -k 10
# 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"}'# 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
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
# 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
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A lightweight plugin that integrates Pinecone vector database capabilities directly into Claude Code, enabling semantic search, index management, and RAG (Retrieval Augmented Generation) workflows.
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