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TsvetanG2

cognigy-ai-mcp-management-server

create_connection

Set up a new Cognigy.AI connection to securely integrate external services by storing API keys and credentials. Validate with dryRun before creating.

Instructions

Creates a new Cognigy.AI connection for external service integration. Connections securely store credentials like API keys, passwords, and tokens. MUTATING: Set dryRun=false to create.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesName for the connection
typeYesConnection type (from extension schema, e.g., 'http-basic-auth', 'api-key', etc.)
dryRunNoIf true (default), validates without creating. Set to false to actually create.
fieldsNoConnection field values as key-value pairs (e.g., { apiKey: '...', baseUrl: '...' })
projectIdYesThe project ID to create the connection in
Behavior4/5

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

Annotations already show readOnlyHint=false (mutating), but description adds valuable context by highlighting the dryRun parameter to prevent accidental creation, and labeling it as MUTATING. No contradiction with annotations.

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?

Two concise sentences, front-loaded with primary action. Every statement adds value, no filler.

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?

Adequate for a create tool with good annotations and schema. Could mention return value (connection ID) but not essential given clear purpose.

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 has 100% coverage with descriptions for all 5 parameters. Description adds general context about storing credentials but no additional details per parameter beyond schema.

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?

Clearly states 'Creates a new Cognigy.AI connection for external service integration'. Verb 'creates' with resource 'connection'. Sibling tools like list_connections, get_connection, update_connection, delete_connection are distinct, so no confusion.

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?

Explicitly notes that connections store credentials (API keys, passwords, tokens) and mentions safety with dryRun parameter. Provides clear context for when to use this tool (creating connections) but doesn't exclude alternatives or mention prerequisites.

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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