Skip to main content
Glama
deepset-ai

deepset-mcp

Official
by deepset-ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

update_deployment

Change a deployment's metadata, sizing, or execution mode. Provide only the fields to update; omitted fields stay as-is.

Instructions

Updates a deployment's metadata, sizing, or execution mode.

Only fields you provide are changed; omitted fields keep their current value. :param deployment_id: ID of the deployment to update. :param name: New name for the deployment. :param description: New description. :param group_label: New group label. :param deployment_mode: New execution mode, "MANAGED" or "SERVERLESS". :param service_level: New sizing tier, "PRODUCTION", "DEVELOPMENT", or "CUSTOM". :param idle_timeout_in_seconds: New idle timeout, in seconds. :param min_query_replica_count: New minimum number of query replicas. :param max_query_replica_count: New maximum number of query replicas. :param max_index_replica_count: New maximum number of index replicas. :param cpu_request: New requested CPU per replica. :param cpu_limit: New CPU limit per replica. :param memory_request: New requested memory per replica. :param memory_limit: New memory limit per replica. :param gpu_limit_gigabyte: New GPU memory limit in gigabytes. :returns: The updated deployment or error message.

All parameters accept object references in the form @obj_id or @obj_id.path.to.value.

Examples::

# Direct call with values
update_deployment(data={'key': 'value'}, threshold=10)

# Call with references
update_deployment(data='@obj_123', threshold='@obj_456.config.threshold')

# Mixed call
update_deployment(data='@obj_123.items', threshold=10)The output is automatically stored and can be referenced in other functions.

Returns a formatted preview with an object ID (e.g., @obj_123). Use the object store tools in combination with the object ID to view nested properties of the object. Use the returned object ID to pass this result to other functions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
cpu_limitNo
cpu_requestNo
descriptionNo
group_labelNo
memory_limitNo
deployment_idYes
service_levelNo
memory_requestNo
deployment_modeNo
gpu_limit_gigabyteNo
idle_timeout_in_secondsNo
max_index_replica_countNo
max_query_replica_countNo
min_query_replica_countNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.27

TDQS

B3/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full burden. It does disclose meaningful patch semantics ('Only fields you provide are changed') and the return shape, but it says nothing about authorization, reversibility, or side effects. Worse, the examples reference parameters ('data', 'threshold') that do not exist on this tool, leaking generic boilerplate that could actively mislead an agent.

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 purpose and patch-semantics statements are front-loaded and efficient, and the parameter list is scannable. However, the trailing object-reference examples and object-store narrative are boilerplate that does not match this tool's parameters and dilutes the signal.

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?

For a 15-parameter mutation tool with no annotations and no output schema, the description does a fair job covering parameters, mutation semantics, and the return value. It still omits permission requirements, error/conflict behavior, and any routing to related deployment tools, and the mismatched examples leave an agent with unresolved questions.

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 description coverage is 0%, so the description must compensate, and it largely does: it enumerates the allowed values for deployment_mode and service_level and gives units for idle_timeout_in_seconds and gpu_limit_gigabyte. Many entries merely restate the schema titles ('New name for the deployment'), and formats for cpu/memory strings remain unstated, keeping it out of 5 territory.

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?

States a specific verb and resource ('Updates a deployment') and names the three updateable areas (metadata, sizing, execution mode), which lets an agent distinguish it from read tools like get_deployment and lifecycle tools like activate_deployment. It does not explicitly differentiate from siblings such as create_deployment_revision or update_index, so it stops short of a 5.

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?

There is no statement of when to use this tool versus alternatives, nor prerequisites such as required permissions or deployment state. The only contextual hint is the patch-like note that omitted fields keep their current value, which is behavioral rather than routing guidance.

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

Deploy Server

Other Tools