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cli

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, ba

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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 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.

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

Voir la source ↗

Métadonnées du fichier

name: 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.

Voir le texte original

---
name: 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.
---

# 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)
```bash
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).

### Authenticate

```bash
# 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.

### 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:

```bash
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.):
```bash
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
```bash
jq -c '.embedding' doc.json | pc index vector query -n my-index --vector - -k 10
```

### Bulk metadata update with preview
```bash
# 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
```bash
# 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
```bash
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
```bash
# 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](references/command-reference.md) — all commands with flags and examples
- [Troubleshooting & best practices](references/troubleshooting.md)

## Documentation

- [CLI Quickstart](https://docs.pinecone.io/reference/cli/quickstart)
- [Command Reference](https://docs.pinecone.io/reference/cli/command-reference)
- [Authentication](https://docs.pinecone.io/reference/cli/authentication)
- [Target Context](https://docs.pinecone.io/reference/cli/target-context)
- [GitHub Releases](https://github.com/pinecone-io/cli/releases)

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Licence: MIT
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Réviser avant installation: Éviter l’installation automatique

Licence: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Low GitHub adoption signal
L’approbation de revue IA est absente
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 23 GitHub stars
Stars/forks activity: 23 stars, 2 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

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Commencer par une petite tâche

1Lisez la source et confirmez entrées, résultats, dépendances et permissions.
2Demandez un plan à l’agent. Approuvez la configuration et les coûts avant un test isolé.
3Vérifiez résultats et fichiers modifiés. Signalez uniquement ce qui a été exécuté et conservez la révision source.

Vérifiez les dépendances, clés API et frais externes dans la source. Un dépôt public ne rend pas tous les services gratuits.

Source et conseils d’utilisation

RépertoriéContrôle statique

Métadonnées et examens sont indicatifs. Popularité, découverte et exécution réussie sont des faits distincts.

Dépôt source: pinecone-io/gemini-cli-extension
Licence: MIT
Version: Unknown
Dernier push GitHub: 14 août 2026
Registre mis à jour: 13 sept. 2026
Chemin des instructions: skills/cli/SKILL.md @ de6792954ae2

Version déclarée dans le registre ; vérifiez les versions de la source.

Qualité

52/100

Revue nécessaire

Confiance

55/100

Do not auto-install

Audit

67/100

Revue nécessaire

Ouvrir l’audit complet Voir le rapport d’évaluation

Dependency or permission surface needs review
Permission surface may require sandboxing
Low GitHub adoption signal
L’approbation de revue IA est absente
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 23 GitHub stars
Stars/forks activity: 23 stars, 2 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

Verified installs: —
Résultats: —

Copier ne signifie pas installer. Les compteurs nécessitent un rapport de réussite et ne garantissent pas la qualité globale.

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    "teams that need a vendor-supported SLA",
    "production agents without a repository review",
    "Low GitHub adoption signal",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "AI review approval is missing",
    "Quality score needs review"
  ],
  "agent_contract": {
    "task_input": "Use cli in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 63/100 Manual review",
      "Audit: 67/100 Needs review",
      "Safety: 19/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "pinecone-io-cli (cli)",
      "install_command": "npx skills add pinecone-io/gemini-cli-extension --skill cli",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "pinecone-io-cli",
      "task": "Use cli in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/pinecone-io-cli",
    "api": "https://www.openagentskill.com/api/agent/skills/pinecone-io-cli",
    "audit": "https://www.openagentskill.com/skills/pinecone-io-cli/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=pinecone-io-cli&task=Use%20cli%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20cli%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20cli%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/pinecone-io-cli/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/pinecone-io-cli"
  }
}

Pour le créateur

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Cette fiche a été indexée à partir de sources publiques et n’est pas marquée officielle tant qu’une revendication de mainteneur n’est pas approuvée.

Créateur: pinecone-io
Source: pinecone-io/gemini-cli-extension
Indexé par: Index communautaire OpenAgentSkill

L’attribution renvoie au dépôt public ou au profil du créateur. Les créateurs peuvent revendiquer la fiche pour mettre à jour les signaux de propriété.

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