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commit_offset

Move Kafka consumer group offsets by partition, timestamp, or earliest/latest, previewing skipped or replayed messages before applying changes with explicit confirmation.

Instructions

Move 1 to 100 consumer group positions in one call through items. Each item names a group and topic and exactly one target: offset (one partition, the next offset the group reads), timestamp (RFC3339; each partition moves to its first message at or after that time, which is how messages are replayed since a moment), or position (earliest or latest). With timestamp or position, omit partition to move every partition of the topic. Moving one offset is an items array of length one.

The response previews, per partition and in total, how many messages each move would skip or replay. No change is made unless confirm is true; one confirm covers the whole batch, and applying is not atomic because Kafka cannot roll back commits that succeeded before a later item failed. Results follow items order, each carrying index with result or error.

Active groups are refused unless allow_active_members is set on the item, because running consumers may overwrite the commit. Requires Kafka offset-commit permission.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYesThe moves to make, 1 to 100 of them. Moving one offset is an array of length one. Two items that would move the same group, topic and partition, including a whole-topic item and a partition item, are refused before anything changes.
confirmNoOptional. When false or omitted, nothing is changed and the response describes what would happen for every item. Must be true to actually move the offsets. One confirm covers the whole batch.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
atomicYes
failedYes
appliedYes
resultsYes
succeededYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well: dry-run by default with preview counts of skipped/replayed messages, a single whole-batch confirm, explicit non-atomicity because Kafka cannot roll back already-successful commits, refusal of active groups, and the required offset-commit permission. These are exactly the behavioral risks an agent must know before calling.

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

Conciseness4/5

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

Front-loaded with the core action in the first sentence, then layered behavior, then constraints. It runs four dense paragraphs and restates some schema content (length-one array, exactly-one-of), but nearly every sentence contributes operational meaning rather than filler.

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?

An output schema exists, so the description need not catalog return fields; it still usefully characterizes the response as a per-partition and total preview and as index-ordered result-or-error entries. Combined with the permission, confirmation, and atomicity disclosures, nothing needed to call this correctly is missing.

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 per-field docs already define offset, timestamp, position, partition, and allow_active_members. The description adds value beyond that by tying the fields into item-level semantics: exactly one target per item, whole-topic vs partition behavior, batch ordering of results by index, and one confirm governing the entire array.

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?

States a specific verb and resource (move consumer group positions) and immediately scopes it to batch semantics via items. It is trivially distinguishable from siblings like describe_consumer_group, consumer_lag, and delete_consumer_group, which never mutate committed offsets.

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?

Gives clear guidance on which of the three mutually exclusive targets to choose and why (timestamp for replaying since a moment, position for earliest/latest, offset for a single partition), plus the omit-partition rule for whole-topic moves. It stops short of explicitly naming sibling tools or stating when not to use it, so it is strong context rather than full when/when-not routing.

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