agentmods.dev

vector-collection-management

vector-collection-management is a skill for Claude Code, Codex from Knuckles-Team/vector-mcp. It costs 123 tokens per session (1,054 once invoked), scanned A, original, MIT.

A guide for managing vector-store collections, which are named indexes containing document pieces used for retrieval-augmented generation (RAG). It works through the vector-mcp server.

In plain words
What is it for?
Use it to create collections, add documents from folders, files, URLs, or text, list existing collections, and delete collections.
Why use it?
It removes the need to remember separate procedures for creating, filling, listing, and deleting document collections.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 16repo +1 changed 2d ago A scan SkillSpector: pass 123 tokens original MIT

Good fit Use it to create collections, add documents from folders, files, URLs, or text, list existing collections, and delete collections.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/knuckles-team/vector-mcp/vector-collection-management
View source ↗ Knuckles-Team/vector-mcp
Install

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.

Any agent
npx skills add Knuckles-Team/vector-mcp --skill vector-collection-management
Clone the repo
git clone --depth 1 https://github.com/Knuckles-Team/vector-mcp

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for vector-collection-management

README.md
[![agentmods](https://agentmods.dev/badge/skills/knuckles-team/vector-mcp/vector-collection-management/github.svg)](https://agentmods.dev/skills/knuckles-team/vector-mcp/vector-collection-management)
Your own site
<a href="https://agentmods.dev/skills/knuckles-team/vector-mcp/vector-collection-management"><img src="https://agentmods.dev/badge/skills/knuckles-team/vector-mcp/vector-collection-management/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for vector-collection-management

Your own site · 80×15
<a href="https://agentmods.dev/skills/knuckles-team/vector-mcp/vector-collection-management"><img src="https://agentmods.dev/badge/skills/knuckles-team/vector-mcp/vector-collection-management.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 123 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,054 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00123 $0.01054
Opus 5.5 $0.00049 $0.00422
Sonnet 5.5 $0.00025 $0.00211
Haiku 4.5 $0.00012 $0.00105

Measured 2d ago against content hash ea8c8eb68099, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

vector-collection-management 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.

vector_mcp/skills/vector-collection-management/SKILL.md · 98 lines

How it starts

The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Vector Collection Management

Lifecycle operations on vector-store collections — the named indexes that hold embedded document chunks — via the vector-mcp MCP server. One condensed, action-routed tool covers create / add / list / delete so the same call shape works across every backend.

When to use

  • Create (or get-or-create) a collection to hold a corpus for RAG.
  • Ingest documents into a collection — from a document_directory, a list of document_paths (files/URLs), or inline document_contents strings.
  • List the collections that exist on a backend.
  • Delete a collection you no longer need.

When NOT to use

  • Querying / retrieving from a collection → vector-hybrid-search.
  • Picking a backend, wiring host/port/credentials, or comparing engines → vector-backend-operations.
  • Persisting derived knowledge into the epistemic-graph KG → this is a vector backend, not a KG source; use the arbora tools for KG writes.

Prerequisites & environment

Connect via the mcp-client skill against the vector-mcp MCP server. Every action takes the connection parameters inline (or falls back to server defaults):

Parameter Notes
db_type Backend: chromadb, postgres, qdrant, couchbase, mongodb
db_path On-disk path (e.g. for embedded chromadb)
host / port Networked backends
db_name / username / password Auth for postgres / couchbase / mongodb
collection_name Target collection (defaults to memory in the retriever)

Embedding is handled server-side by the configured embedding model (agent-connector-sdk embedding client (OpenAI-compatible or Ollama)).

Tools & actions

Condensed tool Actions
vector_collection_management create_collection, add_documents, delete_collection, list_collections

Key parameters

  • overwrite — on create_collection, replace an existing collection instead of get-or-create.
  • document_directory / document_paths / document_contents — the three mutually-usable ingestion inputs for create_collection and add_documents.
  • confirm — required guard on delete_collection.

Read the full file on GitHub · 98 lines

Changes

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.

  1. 2d ago Changed ea8c8eb68099
  2. 1mo ago First seen · 98 lines · 123 tokens per session scan A 0de42dabdc2e

Subscribe to this mod's changes

vector-collection-management is a skill published in the GitHub repository Knuckles-Team/vector-mcp (16 stars, last pushed yesterday), licensed MIT. It adds 123 tokens to every session and 1,054 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Data and AIDatabasesMongoDBRAG and vectorschromadbcollectionscouchbaseembeddingsmcpmcp-servermongodb-atlaspgvectorvector
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