Skip to main content
Glama
TsvetanG2

cognigy-ai-mcp-management-server

merge_package

Merge selected resources from a package into a Cognigy.AI project with locale mapping. Validate with dry run or perform the merge operation.

Instructions

Merges a package into a Cognigy.AI project, importing selected resources. Use localeMapping to map package locales to project locales. MUTATING: Set dryRun=false to merge. Async operation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dryRunNoIf true (default), validates without merging. Set to false to actually merge. WARNING: This modifies the target project!
packageIdYesThe package ID to merge
timeoutMsNoMaximum time to wait for merge (5-600 seconds, default 180)
strategiesNoOptional conflict resolution strategies per resource type
resourceIdsYesArray of resource IDs from the package to import
localeMappingYesMapping of package locales to project locales
pollIntervalMsNoHow often to check task status (1-10 seconds, default 3)
Behavior5/5

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

Explicitly labels 'MUTATING' and warns in schema: 'WARNING: This modifies the target project!' Also states 'Async operation.' Annotations don't contradict; they align.

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?

Three concise sentences with no fluff. Each sentence adds value: purpose, locale mapping, mutation/async warning.

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

Completeness4/5

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

Covers main aspects: purpose, key parameters, mutation, async. No output schema, but async operation implies task result. Could mention return type but sufficient for agent.

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%. Description repeats schema info but doesn't add new meaning beyond 'use localeMapping' and dryRun guidance. Baseline 3 is appropriate.

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?

First sentence states 'Merges a package into a Cognigy.AI project, importing selected resources.' This is a specific verb+resource, distinguishing from sibling tools like list_packages or create_package.

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?

Provides clear guidance on using localeMapping and setting dryRun=false for actual merge. Implicitly suggests use when need to import resources from a package, but no explicit when-not or alternatives.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/TsvetanG2/cognigy-ai-mcp-management-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server