Skip to main content
Glama
AceDataCloud

AiChat MCP Server

Official

aichat_create_conversation

Send a question to AI models such as GPT-4, DeepSeek, or Grok and receive generated answers. Continue existing conversations by providing a conversation ID.

Instructions

Create an AI conversation using the AiChat API.

Sends a question to the specified AI model and returns the generated answer.
Supports a wide range of models including GPT-4, GPT-5, o-series, DeepSeek, Grok, and GLM.

Use this when:
- You need to ask a question to an AI model
- You want to continue an existing conversation (provide conversation_id)
- You need answers from specific AI models like DeepSeek, Grok, or GLM

Returns:
    JSON response containing the conversation ID and the generated answer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoThe model to use for generating the answer. Options include gpt-4.1, gpt-4o, gpt-5, o1, o3, o4-mini, deepseek-r1, deepseek-v3, grok-3, glm-4.7, and many more. Default is gpt-4.1.gpt-4.1
presetNoAn optional preset model configuration to apply for this conversation.
questionYesThe prompt or question to be answered by the AI model. Required.
statefulNoWhether to use stateful conversation mode. When True, the server tracks conversation history. Default is False (stateless).
referencesNoOptional list of reference sources or context to include when generating the answer.
conversation_idNoThe unique identifier of an existing conversation to continue. If provided, the AI will respond in the context of the prior conversation. Leave empty to start a new conversation.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries full burden. It discloses the return format (JSON with conversation ID and answer) but fails to mention side effects, rate limits, authentication requirements, or any destructive behavior. For a creation tool, more behavioral context is needed.

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 moderately structured with paragraphs and a bullet-like list, but it includes some verbosity (e.g., model list recap). It could be more concise while retaining key information.

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

Completeness3/5

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

Given the presence of an output schema and full parameter descriptions, the description covers primary use cases (new conversation, continuation) but does not explain stateful behavior, preset usage, or error handling. It is adequate for straightforward usage.

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 description adds marginal value. It reinforces that 'question' is the prompt and mentions continuing conversations via conversation_id, but the schema descriptions already provide sufficient meaning. Baseline 3 is appropriate.

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 it creates an AI conversation, sends a question to a model, and returns an answer. It mentions continuing existing conversations and supporting various models, but does not differentiate from the sibling tool aichat_create_conversation_v2.

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

Usage Guidelines3/5

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

The description includes explicit 'Use this when:' bullets covering common scenarios, but lacks guidance on when not to use this tool or alternatives (e.g., v2). No exclusions or when-not cases are provided.

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/AceDataCloud/AiChatMCP'

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