Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/pinecone-io/gemini-cli-extension/clinpx skills add pinecone-io/gemini-cli-extension --skill cligit clone --depth 1 https://github.com/pinecone-io/gemini-cli-extensionWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00072 | $0.01471 |
| Opus 5 | $0.00036 | $0.00736 |
| Sonnet 5 | $0.00014 | $0.00294 |
| Haiku 4.5 | $0.00007 | $0.00147 |
Grade A, and why
cli scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
95% identical to pinecone:cli — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pinecone CLI (pc)
Manage Pinecone from the terminal. The CLI is especially valuable for vector operations across all index types — something the MCP currently can't do.
CLI vs MCP
| CLI | MCP | |
|---|---|---|
| Index types | All (standard, integrated, sparse) | Integrated only |
| Vector ops (upsert, query, fetch, update, delete) | ✅ | ❌ |
| Text search on integrated indexes | ✅ | ✅ |
| Backups, namespaces, org/project mgmt | ✅ | ❌ |
| CI/CD / scripting | ✅ | ❌ |
Setup
Install (macOS)
brew tap pinecone-io/tap
brew install pinecone-io/tap/pinecone
Other platforms (Linux, Windows) — download from GitHub Releases.
Authenticate
# Interactive (recommended for local dev)
pc login
pc target -o "my-org" -p "my-project"
# Service account (recommended for CI/CD)
pc auth configure --client-id "$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 |
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 156 lines · 72 tokens per session scan A bb54e8fff99b
cli is a skill published in the GitHub repository pinecone-io/gemini-cli-extension (23 stars, last pushed 18d ago), licensed MIT. It adds 72 tokens to every session and 1,471 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to pinecone:cli, differing in 4 lines, and is treated as a copy.
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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…
pinecone:mcp
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