Execute custom aggregation pipelines on MongoDB collections to filter, group, transform, and compute aggregated results from document data.
Run an aggregation pipeline
| Name | Required | Description | Default |
|---|---|---|---|
| pipeline | Yes | Aggregation pipeline stages | |
| collection | Yes | Collection name |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden of behavioral disclosure. It only states the operation type without revealing whether results are returned as a stream, a single document, or aggregated values, and it omits side effects, authorization needs, or performance considerations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and direct, but it is under-specified rather than efficiently informative. It conveys the core action in one clause but provides no additional structured detail that would help an agent use the tool correctly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description should explain return behavior, pipeline expectations, and usage context. It does none of that, so the agent is left without enough information to confidently predict the outcome of invoking this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully documents both parameters with descriptions, so the schema carries the semantic weight. The description adds no parameter-level meaning, which is acceptable given the 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific operation, running an aggregation pipeline, which is distinct from sibling tools like find, count, and list_collections. It is clear about the action and resource, though it does not explicitly contrast itself with siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use aggregate versus find, count, or list_collections. The description does not mention use cases, limitations, or alternatives, leaving the agent to infer the appropriate context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.