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LaunchNotes MCP Server

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Search LaunchNotes Feedback

launchnotes_search_feedback
Read-onlyIdempotent

Search and filter customer feedback in a LaunchNotes project by sentiment, importance, state, or keywords. Retrieve feedback items with customer details and timestamps.

Instructions

Search and filter customer feedback in a LaunchNotes project.

Args:

  • project_id (string): The ID of the project (required)

  • query (string, optional): Search term to find in feedback content

  • reaction ('happy' | 'meh' | 'sad', optional): Filter by customer sentiment

  • importance ('low' | 'medium' | 'high', optional): Filter by importance level

  • organized_state (string, optional): Filter by state ('organized', 'unorganized', 'announcement', 'idea', 'roadmap')

  • starred (boolean, optional): Filter by starred status

  • archived (boolean, optional): Filter by archived status

  • limit (number, optional): Number to return (max 100, default: 20)

  • response_format ('json' | 'markdown'): Output format (default: 'markdown')

Returns: List of feedback items with content, sentiment, importance, customer info, and timestamps

Use Cases:

  • "What are customers saying about Digests?"

  • "Show me all unhappy feedback"

  • "Find high importance feedback that's unorganized"

  • "Search feedback containing 'API integration'"

  • "Show me starred feedback"

Error Handling:

  • Returns "Project not found" if project ID doesn't exist

  • Returns "Authentication failed" if API token is invalid

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYesThe ID of the LaunchNotes project
queryNoSearch term to find in feedback content
reactionNoFilter by customer reaction/sentiment
importanceNoFilter by importance level
organized_stateNoFilter by organized state: 'organized', 'unorganized', 'announcement', 'idea', 'roadmap'
starredNoFilter by starred status
archivedNoFilter by archived status
limitNoNumber of feedback items to return (max 100)
response_formatNoOutput format: 'json' for structured data, 'markdown' for human-readablemarkdown
Behavior4/5

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

The description adds error handling details ('Project not found', 'Authentication failed') and return structure, which supplement the annotations (readOnlyHint, destructiveHint). The annotations already indicate safe read-only behavior, so the description provides meaningful but not essential extra context.

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?

The description is well-structured into Args, Returns, Use Cases, and Error Handling sections. It is front-loaded with the core purpose, and every sentence provides clear, non-redundant information. There is no wasted text.

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?

Given the tool has 9 parameters, no output schema, and moderate complexity, the description covers all essential aspects: purpose, all parameters, return format, use cases, and error handling. It provides enough context for an agent to correctly select and invoke the tool.

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

Parameters3/5

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

Schema coverage is 100%, so the schema already documents all parameters. The description's Args section mostly mirrors the schema, though it adds default values (limit default 20) and output format options. This adds marginal clarity beyond the structured schema, meeting the baseline without exceeding it.

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?

The description explicitly states 'Search and filter customer feedback in a LaunchNotes project' with a clear verb and resource. The use cases (e.g., 'What are customers saying about Digests?') further solidify the purpose, distinguishing it from sibling tools like `launchnotes_get_feedback` which retrieves a single item.

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?

The description includes a 'Use Cases' section with practical examples (e.g., 'Show me all unhappy feedback'), indicating appropriate contexts. However, it does not explicitly state when not to use this tool or mention alternative tools, leaving some ambiguity for agents unfamiliar with the sibling set.

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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