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AceDataCloud

AiChat MCP Server

Official

aichat_create_conversation_v2

Create and manage AI conversations with multiple models including GPT-4, Claude, DeepSeek, and more. Supports chat, retrieve, update, and delete actions with stateful conversation mode.

Instructions

Create/manage conversations via AiChat v2 endpoint.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoConversation ID. Required for retrieve/update/delete actions.
limitNoPagination limit for retrieve_batch.
modelNoModel to use for the request.gpt-4.1
titleNoConversation title.
actionNoOperation to perform: chat (default), retrieve, retrieve_batch, update, or delete.chat
offsetNoPagination offset for retrieve_batch.
presetNoOptional preset model configuration.
messageNoSingle message object to include in the request.
user_idNoFilter or associate by user ID.
messagesNoConversation messages for update/action workflows.
questionNoQuestion text for chat action.
statefulNoWhether to use stateful conversation mode.
max_turnsNoMaximum number of turns for conversation history.
referencesNoOptional list of reference sources.
model_groupNoProvider group filter for retrieve_batch.
tool_resultsNoTool call results for follow-up turns.
application_idNoFilter or associate by application ID.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description must disclose key behavioral traits but fails to mention that the tool supports multiple actions beyond creation, or any side effects, authentication, or rate limits.

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 concise but too sparse for a tool with 17 parameters and multiple actions. It lacks essential details without being verbose.

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?

Given the high complexity (17 parameters, multiple actions, existing output schema), the description is woefully incomplete, leaving the agent to infer behavior solely from the schema.

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 description coverage is 100%, so baseline is 3. The description adds no extra meaning beyond what is already in the schema.

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

Purpose3/5

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

The description 'Create/manage conversations' vaguely indicates purpose but is ambiguous about the multiple actions supported (chat, retrieve, update, delete). It does not clearly distinguish from sibling 'aichat_create_conversation'.

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?

No usage guidance is provided. The description does not explain when to use this tool over siblings or indicate prerequisites, leading to potential misuse.

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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