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Vector Search endpoints

manage_vs_endpoint
Destructive

Manage Vector Search endpoints by listing, getting, creating, updating, or deleting them to control compute for vector indexes.

Instructions

Manage Vector Search endpoints (the compute that hosts vector indexes).

Actions:

  • list / get: endpoint state, type, number of indexes, tags.

  • create: name + endpoint_type; optional spec {budget_policy_id, target_qps, usage_policy_id}. Provisioning is long-running: returns status 'pending' unless wait_seconds is set.

  • update: spec with any of target_qps, budget_policy_id, custom_tags ({key: value} - replaces all tags).

  • delete: permanently delete the endpoint (requires confirm).

Safety classification: list, get = READ_ONLY; create, update = WRITE; delete = DESTRUCTIVE.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoEndpoint name (all actions except list).
specNoRequest body fields for create/update, using the Databricks REST API field names (snake_case). Unknown fields are rejected.
actionYesOperation to perform.
confirmNoSet to true ONLY after the user has reviewed the plan returned by a previous call with status 'confirmation_required'. Required for destructive/security-sensitive actions.
dry_runNoIf true, validate and return the planned change without executing it.
page_sizeNoMax items to return (server caps this).
page_tokenNonext_page_token from a previous response.
wait_secondsNoOptionally wait up to this many seconds for the endpoint to come ONLINE (capped by the server's max wait). Default: return immediately with status 'pending'.
endpoint_typeNocreate: endpoint type.STANDARD

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
pageNo
planNo
toolYes
actionNo
safetyNo
statusNosuccess
summaryYes
warningsNo
next_stepsNoSuggested follow-up calls.
request_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Goes well beyond the annotations by classifying per-action safety (list/get = READ_ONLY, create/update = WRITE, delete = DESTRUCTIVE), disclosing that provisioning is long-running and returns 'pending', that delete requires confirm, and that update's custom_tags REPLACES all tags. This is exactly the extra context annotations alone can't convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Bulleted by action with a compact spec summary, then a one-line safety classification. Every line carries information and the scan order (actions first, safety last) is sensible.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return values need not be described, and the description covers the remaining gaps an agent needs: long-running provisioning, confirm gating, dry_run semantics, and per-action risk. Nothing material is missing for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning: which spec fields apply to create vs update, that custom_tags overwrites existing tags, the confirm workflow tied to 'confirmation_required', and the wait_seconds default behavior. Only the pagination params (page_size/page_token) are left to the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Opens with a specific verb+resource and parenthetically explains what an endpoint is ('the compute that hosts vector indexes'). The action enumeration (list/get/create/update/delete) makes it immediately distinguishable from siblings like manage_vs_index or query_vs_index.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Each action is annotated with required inputs and behavior, and it explains when to set wait_seconds (only if you want to block for ONLINE) versus taking the immediate 'pending' return. It does not explicitly route the agent when to pick this over manage_vs_index/manage_vs_data, so it stops short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.