Can I use Pinecone as a CLI?

Yes. KosmoKrator exposes a Pinecone CLI through kosmo integrations:call and the provider shortcut command. Commands can return JSON for scripts, CI, and coding agents.

Can I expose Pinecone through MCP?

Yes. The KosmoKrator MCP gateway can expose selected Pinecone tools to clients such as Claude Code, Cursor, Codex, and other MCP-compatible tools.

Where are Pinecone credentials stored?

Pinecone credentials are configured in KosmoKrator's local integration settings and reused by CLI, Lua, and MCP gateway surfaces.

Can I deny write access for Pinecone MCP tools?

Yes. Start the gateway with --write=deny for read-only clients, or use ask/allow only for trusted workspaces.

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Pinecone CLI for AI Agents

Use the Pinecone CLI from KosmoKrator to call Pinecone tools headlessly, return JSON, inspect schemas, and automate workflows from coding agents, scripts, and CI.

Pinecone CLI Setup

Pinecone can be configured headlessly with `kosmokrator integrations:configure pinecone`.

Install, configure, and verify

# Install KosmoKrator first if it is not available on PATH.
curl -fsSL https://raw.githubusercontent.com/OpenCompanyApp/kosmokrator/main/install.sh | bash

# Configure and verify this integration.
kosmokrator integrations:configure pinecone --set api_key="$PINECONE_API_KEY" --enable --read allow --write ask --json
kosmokrator integrations:doctor pinecone --json
kosmokrator integrations:status --json

Credentials

Authentication type: API key api_key. Configure credentials once, then reuse the same stored profile from scripts, coding CLIs, Lua, and MCP.

Key	Env var	Type	Required	Label
`api_key`	`PINECONE_API_KEY`	Secret `secret`	yes	API Key
`url`	`PINECONE_URL`	URL `url`	no	Pinecone API URL
`api_version`	`PINECONE_API_VERSION`	Text `text`	no	API Version

Command Patterns

The generic command is stable across every integration. The provider shortcut is shorter for humans.

Generic CLI call

kosmo integrations:call pinecone.pinecone_list_indexes '{}' --json

Provider shortcut

kosmo integrations:pinecone pinecone_list_indexes '{}' --json

Discovery

These commands return structured output for coding agents that need to inspect capabilities before choosing a function.

Discovery commands

kosmo integrations:docs pinecone --json
kosmo integrations:docs pinecone.pinecone_list_indexes --json
kosmo integrations:schema pinecone.pinecone_list_indexes --json
kosmo integrations:search "Pinecone" --json
kosmo integrations:list --json

Automation Contexts

The same configured command surface works in these environments. The command does not change unless the host wrapper, credentials, or permissions change.

CI Run integration calls from CI jobs with JSON output, explicit credentials, and predictable exit status. Cron Jobs Schedule repeatable integration workflows from cron while keeping credentials in KosmoKrator config. Shell Scripts Call integration functions from shell scripts with stable JSON input and output. Headless Automation Use KosmoKrator as a non-interactive integration runtime for local automations and wrappers. Coding Agents Let coding agents discover schemas and execute integration functions through CLI commands or MCP.

CLI Functions

Every function below can be called headlessly. Commands are highlighted, copyable, and scroll horizontally when payloads are long.

`pinecone.pinecone_list_indexes`

List all vector indexes in your Pinecone project. Returns index names, dimensions, metrics, and status.

Read read

Parameters: none

Generic call

kosmo integrations:call pinecone.pinecone_list_indexes '{}' --json

Shortcut

kosmo integrations:pinecone pinecone_list_indexes '{}' --json

`pinecone.pinecone_get_index`

Get detailed information about a specific Pinecone vector index, including its dimension, metric, host URL, and status.

Read read

Parameters: name

Generic call

kosmo integrations:call pinecone.pinecone_get_index '{"name":"example_name"}' --json

Shortcut

kosmo integrations:pinecone pinecone_get_index '{"name":"example_name"}' --json

`pinecone.pinecone_create_index`

Create a new serverless vector index in Pinecone. Specify the index name, vector dimension, and similarity metric (cosine, euclidean, or dotproduct).

Write write

Parameters: name, dimension, metric, cloud, region

Generic call

kosmo integrations:call pinecone.pinecone_create_index '{"name":"example_name","dimension":1,"metric":"example_metric","cloud":"example_cloud","region":"example_region"}' --json

Shortcut

kosmo integrations:pinecone pinecone_create_index '{"name":"example_name","dimension":1,"metric":"example_metric","cloud":"example_cloud","region":"example_region"}' --json

`pinecone.pinecone_configure_index`

Configure an existing Pinecone index, such as deletion protection, tags, or supported scaling settings.

Write write

Parameters: name, config

Generic call

kosmo integrations:call pinecone.pinecone_configure_index '{"name":"example_name","config":"example_config"}' --json

Shortcut

kosmo integrations:pinecone pinecone_configure_index '{"name":"example_name","config":"example_config"}' --json

`pinecone.pinecone_delete_index`

Delete a Pinecone index by name. Deletion protection must be disabled on the index first.

Write write

Parameters: name

Generic call

kosmo integrations:call pinecone.pinecone_delete_index '{"name":"example_name"}' --json

Shortcut

kosmo integrations:pinecone pinecone_delete_index '{"name":"example_name"}' --json

`pinecone.pinecone_upsert_vectors`

Upsert vectors into a Pinecone index using an index host URL.

Write write

Parameters: index_host, vectors, namespace

Generic call

kosmo integrations:call pinecone.pinecone_upsert_vectors '{"index_host":"example_index_host","vectors":"example_vectors","namespace":"example_namespace"}' --json

Shortcut

kosmo integrations:pinecone pinecone_upsert_vectors '{"index_host":"example_index_host","vectors":"example_vectors","namespace":"example_namespace"}' --json

`pinecone.pinecone_query_vectors`

Search for similar vectors in a Pinecone index using a query embedding.

Read read

Parameters: index_host, vector, top_k, filter, include_metadata, include_values, namespace

Generic call

kosmo integrations:call pinecone.pinecone_query_vectors '{"index_host":"example_index_host","vector":"example_vector","top_k":1,"filter":"example_filter","include_metadata":true,"include_values":true,"namespace":"example_namespace"}' --json

Shortcut

kosmo integrations:pinecone pinecone_query_vectors '{"index_host":"example_index_host","vector":"example_vector","top_k":1,"filter":"example_filter","include_metadata":true,"include_values":true,"namespace":"example_namespace"}' --json

`pinecone.pinecone_fetch_vectors`

Fetch vectors by ID from a Pinecone index namespace.

Read read

Parameters: index_host, ids, namespace

Generic call

kosmo integrations:call pinecone.pinecone_fetch_vectors '{"index_host":"example_index_host","ids":"example_ids","namespace":"example_namespace"}' --json

Shortcut

kosmo integrations:pinecone pinecone_fetch_vectors '{"index_host":"example_index_host","ids":"example_ids","namespace":"example_namespace"}' --json

`pinecone.pinecone_update_vector`

Update vector values, sparse values, metadata, or filtered metadata in a Pinecone namespace.

Write write

Parameters: index_host, id, values, sparse_values, set_metadata, filter, namespace, dry_run

Generic call

kosmo integrations:call pinecone.pinecone_update_vector '{"index_host":"example_index_host","id":"example_id","values":"example_values","sparse_values":"example_sparse_values","set_metadata":"example_set_metadata","filter":"example_filter","namespace":"example_namespace","dry_run":true}' --json

Shortcut

kosmo integrations:pinecone pinecone_update_vector '{"index_host":"example_index_host","id":"example_id","values":"example_values","sparse_values":"example_sparse_values","set_metadata":"example_set_metadata","filter":"example_filter","namespace":"example_namespace","dry_run":true}' --json

`pinecone.pinecone_delete_vectors`

Delete vectors from a Pinecone namespace by IDs, metadata filter, or delete_all flag.

Write write

Parameters: index_host, ids, filter, delete_all, namespace

Generic call

kosmo integrations:call pinecone.pinecone_delete_vectors '{"index_host":"example_index_host","ids":"example_ids","filter":"example_filter","delete_all":true,"namespace":"example_namespace"}' --json

Shortcut

kosmo integrations:pinecone pinecone_delete_vectors '{"index_host":"example_index_host","ids":"example_ids","filter":"example_filter","delete_all":true,"namespace":"example_namespace"}' --json

`pinecone.pinecone_describe_index_stats`

Describe vector count, dimensions, and namespace statistics for a Pinecone index.

Read read

Parameters: index_host, filter

Generic call

kosmo integrations:call pinecone.pinecone_describe_index_stats '{"index_host":"example_index_host","filter":"example_filter"}' --json

Shortcut

kosmo integrations:pinecone pinecone_describe_index_stats '{"index_host":"example_index_host","filter":"example_filter"}' --json

`pinecone.pinecone_list_collections`

List all collections in your Pinecone project. Collections are static snapshots of indexes used for backups or creating new indexes.

Read read

Parameters: none

Generic call

kosmo integrations:call pinecone.pinecone_list_collections '{}' --json

Shortcut

kosmo integrations:pinecone pinecone_list_collections '{}' --json

Function Schemas

Use these parameter tables when building CLI payloads without calling integrations:schema first.

pinecone.pinecone_list_indexes 0 parameters

Schema command

kosmo integrations:schema pinecone.pinecone_list_indexes --json

Parameter	Type	Required	Description
No parameters.

pinecone.pinecone_get_index 1 parameters

Schema command

kosmo integrations:schema pinecone.pinecone_get_index --json

Parameter	Type	Required	Description
`name`	string	yes	The name of the index to retrieve.

pinecone.pinecone_create_index 5 parameters

Schema command

kosmo integrations:schema pinecone.pinecone_create_index --json

Parameter	Type	Required	Description
`name`	string	yes	The name for the new index. Must be unique within the project.
`dimension`	integer	yes	The dimension size of the vectors to be stored (e.g., 1536 for OpenAI text-embedding-ada-002, 3072 for text-embedding-3-large).
`metric`	string	no	The similarity metric to use: "cosine" (default), "euclidean", or "dotproduct".
`cloud`	string	no	Serverless cloud provider. Defaults to aws.
`region`	string	no	Serverless cloud region. Defaults to us-east-1.

pinecone.pinecone_configure_index 2 parameters

Schema command

kosmo integrations:schema pinecone.pinecone_configure_index --json

Parameter	Type	Required	Description
`name`	string	yes	The index name.
`config`	object	yes	PATCH body for the index configuration.

pinecone.pinecone_delete_index 1 parameters

Schema command

kosmo integrations:schema pinecone.pinecone_delete_index --json

Parameter	Type	Required	Description
`name`	string	yes	The index name to delete.

pinecone.pinecone_upsert_vectors 3 parameters

Schema command

kosmo integrations:schema pinecone.pinecone_upsert_vectors --json

Parameter	Type	Required	Description
`index_host`	string	yes	The index host URL, such as "https://example.svc.us-east-1.pinecone.io".
`vectors`	array	yes	Vector records with id, values, and optional metadata.
`namespace`	string	no	Optional namespace where vectors are upserted.

pinecone.pinecone_query_vectors 7 parameters

Schema command

kosmo integrations:schema pinecone.pinecone_query_vectors --json

Parameter	Type	Required	Description
`index_host`	string	yes	The index host URL.
`vector`	array	yes	Query embedding vector values.
`top_k`	integer	no	Number of top matches to return (default: 10).
`filter`	object	no	Optional metadata filter expression.
`include_metadata`	boolean	no	Whether to include metadata in matches (default: true).
`include_values`	boolean	no	Whether to include vector values in matches (default: false).
`namespace`	string	no	Optional namespace to query.

pinecone.pinecone_fetch_vectors 3 parameters

Schema command

kosmo integrations:schema pinecone.pinecone_fetch_vectors --json

Parameter	Type	Required	Description
`index_host`	string	yes	The index host URL.
`ids`	array	yes	Vector IDs to fetch.
`namespace`	string	no	Optional namespace.

pinecone.pinecone_update_vector 8 parameters

Schema command

kosmo integrations:schema pinecone.pinecone_update_vector --json

Parameter	Type	Required	Description
`index_host`	string	yes	The index host URL.
`id`	string	no	Vector ID for single-record updates.
`values`	array	no	Replacement vector values.
`sparse_values`	object	no	Sparse vector values.
`set_metadata`	object	no	Metadata fields to set.
`filter`	object	no	Metadata filter for bulk metadata updates.
`namespace`	string	no	Optional namespace.
`dry_run`	boolean	no	Return matched count without updating when using a filter.

pinecone.pinecone_delete_vectors 5 parameters

Schema command

kosmo integrations:schema pinecone.pinecone_delete_vectors --json

Parameter	Type	Required	Description
`index_host`	string	yes	The index host URL.
`ids`	array	no	Vector IDs to delete.
`filter`	object	no	Metadata filter selecting vectors to delete.
`delete_all`	boolean	no	Set true to delete all vectors in the namespace.
`namespace`	string	no	Optional namespace.

pinecone.pinecone_describe_index_stats 2 parameters

Schema command

kosmo integrations:schema pinecone.pinecone_describe_index_stats --json

Parameter	Type	Required	Description
`index_host`	string	yes	The index host URL.
`filter`	object	no	Optional metadata filter.

pinecone.pinecone_list_collections 0 parameters

Schema command

kosmo integrations:schema pinecone.pinecone_list_collections --json

Parameter	Type	Required	Description
No parameters.

Permissions

Headless calls still follow the integration read/write permission policy. Configure read/write defaults with integrations:configure. Add --force only for trusted automation that should bypass that policy.