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Glama
AiChat MCP Server

AiChat MCP Server

Official
by AceDataCloud

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
ACEDATACLOUD_API_TOKENYesYour AceDataCloud API token

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
aichat_create_conversationA

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.
aichat_create_conversation_v2C

Create/manage conversations via AiChat v2 endpoint.

aichat_list_modelsA

List all available AI models for the AiChat API.

Returns a comprehensive list of supported models grouped by provider,
including GPT-4/5, o-series, DeepSeek, Grok, and GLM models.

Returns:
    Formatted list of available models with descriptions.
aichat_get_usage_guideA

Get a comprehensive guide for using the AiChat tools.

Provides detailed information on how to use the AiChat tools effectively,
including parameters, examples, and best practices.

Returns:
    Complete usage guide for AiChat tools.

Prompts

Interactive templates invoked by user choice

NameDescription
aichat_guideGuide for choosing the right AiChat tool and model for AI conversation tasks.
aichat_workflow_examplesCommon workflow examples for AiChat tasks.

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

B3.1/5.0

Scored across 4 tools

Disambiguation2/5

aichat_create_conversation and aichat_create_conversation_v2 appear to serve the same core purpose, with the v2 tool lacking a clear description of how it differs. An agent cannot reliably choose between them, though list_models and get_usage_guide are distinct.

Naming Consistency4/5

All tools use a consistent aichat_ prefix and mostly follow a verb_noun pattern such as create_conversation, get_usage_guide, and list_models. The _v2 suffix is a minor deviation but still readable and consistent with versioning conventions.

Tool Count3/5

Four tools is a reasonable count for a lightweight chat API wrapper, but one of them is a duplicate/versioned variant and another is a meta usage guide rather than a core operation. The set feels slightly thin and unevenly scoped.

Completeness3/5

The surface covers creating conversations, listing models, and getting usage guidance, but lacks clear operations for retrieving, listing, or deleting existing conversations. The v2 tool may fill some gaps, but its vague description leaves lifecycle coverage uncertain.

Maintenance

ActivityActive
ResponsivenessNo issues