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Zilliz MCP Server

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by zilliztech

delete_entities

Remove entities from a Milvus vector database collection using filtering conditions or primary keys to manage data efficiently.

Instructions

Delete entities from a collection by filtering conditions or primary keys.

Args:
    cluster_id: ID of the cluster
    region_id: ID of the cloud region hosting the cluster
    endpoint: The cluster endpoint URL. Can be obtained by calling describe_cluster and using the connect_address field
    collection_name: The name of an existing collection
    filter: A scalar filtering condition to filter matching entities. You can set this parameter to an empty string to skip scalar filtering. To build a scalar filtering condition, refer to Reference on Scalar Filters
    db_name: The name of the target database. Pass explicit dbName or leave empty when cluster is free or serverless
    partition_name: The name of a partition in the current collection. If specified, the data is to be deleted from the specified partition
Returns:
    Dict containing the response
    Example:
    {
        "code": 0,
        "cost": 0,
        "data": {}
    }
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cluster_idYes
region_idYes
endpointYes
collection_nameYes
filterYes
db_nameNo
partition_nameNo
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly indicates this is a destructive operation ('Delete'), but doesn't specify whether deletions are permanent/reversible, what permissions are required, rate limits, or error conditions. The example response shows a generic success format but lacks detail on failure modes or side effects. This is inadequate for a mutation tool with zero annotation coverage.

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

Conciseness3/5

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

The description is moderately structured with clear sections (Args, Returns, Example) but contains some redundancy. The 'Returns' section could be more concise, and the example takes significant space without adding critical information beyond the response format. Some parameter explanations (like 'endpoint') are helpful but could be more efficiently integrated.

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

Completeness3/5

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

Given the tool's complexity (7 parameters, destructive operation, no annotations, no output schema), the description is partially complete. It covers parameter meanings well but lacks crucial behavioral context like deletion permanence, authorization requirements, and error handling. The example response provides some output format insight but doesn't substitute for proper behavioral transparency.

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?

The description provides substantial parameter semantics beyond the schema, which has 0% description coverage. It explains the purpose of 'cluster_id', 'region_id', 'endpoint' (including how to obtain it), 'collection_name', 'filter' (with filtering guidance and empty string behavior), 'db_name' (when to use or leave empty), and 'partition_name' (scope of deletion). This compensates well for the schema's lack of descriptions.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Delete entities from a collection by filtering conditions or primary keys.' It specifies the verb ('Delete'), resource ('entities from a collection'), and mechanism ('filtering conditions or primary keys'). However, it doesn't explicitly differentiate this from other destructive operations like 'suspend_cluster' or data modification tools like 'insert_entities'.

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

Usage Guidelines2/5

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

The description provides minimal usage guidance. It mentions that the 'endpoint' parameter 'can be obtained by calling describe_cluster,' which hints at a prerequisite relationship, but doesn't explain when to use this tool versus alternatives like other deletion methods or when deletion is appropriate versus modification. No explicit 'when-not' or alternative tool recommendations are provided.

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

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