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Glama
AceDataCloud

AiChat MCP Server

Official
by AceDataCloud
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

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

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3.1/5.0

Scored across 4 tools

Disambiguation2/5

aichat_create_conversation and aichat_create_conversation_v2 clearly overlap, and the v2 description ('Create/manage conversations via AiChat v2 endpoint') gives no guidance on when to prefer it over v1. An agent cannot reliably choose between the two, and the '_v2' variant's 'manage' scope is undefined.

Naming Consistency4/5

All tools share the aichat_ prefix and a consistent verb_noun pattern (list_models, create_conversation, get_usage_guide). The only deviation is the _v2 suffix on one tool, which is a minor inconsistency.

Tool Count3/5

Four tools is on the thin side for an AI chat API, and one of them (get_usage_guide) is a documentation helper rather than a functional operation. Reasonable but borderline under-scoped.

Completeness3/5

Core chat (create conversation) and discovery (list models) are covered, but conversation lifecycle is incomplete: no get/history, list, or delete conversation operations, and the 'manage' claim in v2 is not backed by distinct tools.

Maintenance

ActivityActive
ResponsivenessNo issues

Resources