Skip to main content
Glama
mundurragacl

Amazon Connect MCP Server

by mundurragacl

config_create_contact_flow

Create a new Amazon Connect contact flow by specifying its name, type, and content, for scenarios like customer queue or hold flows.

Instructions

Create a contact flow. Types: CONTACT_FLOW, CUSTOMER_QUEUE, CUSTOMER_HOLD, etc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
regionNo
contentYes
flow_typeYes
descriptionNo
instance_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations, the description carries the full transparency burden. It indicates a mutating operation ('Create') but does not disclose permissions, reversibility, idempotency, content format expectations, or effects of the 'region' and 'instance_id' parameters. This is a significant gap for a create operation.

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

Conciseness3/5

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

The description is very short and front-loaded with the main verb, but the 'etc.' is a filler that reduces informativeness. While concise, it lacks structured detail that would help an agent parse the key decision points (e.g., enum values, content format). It is appropriately sized but not optimally structured.

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

Completeness2/5

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

For a tool with 6 parameters and an output schema, the description is too minimal. It does not explain the relationship between flow_type and content, the expected format of 'content', or how parameters like 'region' and 'instance_id' influence the operation. The output schema exists but the description still should provide context for the parameters, which it does only for flow_type in a partial way.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It only hints at valid values for 'flow_type' (CONTACT_FLOW, CUSTOMER_QUEUE, CUSTOMER_HOLD) but leaves 'etc.' vague and says nothing about 'name', 'content', 'region', 'description', or 'instance_id'. The meaning of 'content' (likely a flow definition JSON) is completely unexplained, leaving agents to guess.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the core action ('Create a contact flow') with a specific resource, and briefly lists some flow types. It distinguishes from sibling tools like config_list_contact_flows or config_update_contact_flow_content, though it doesn't explicitly name them. The 'etc.' leaves some ambiguity about the full set of types, preventing a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, no prerequisites, and no context about when creating is appropriate. It only mentions the available types, not how to choose between them or when to use update/describe tools instead.

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/mundurragacl/amazon-connect-mcp'

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