grok-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| XAI_API_KEY | No | API Key for xAI (Grok), required for API mode. Obtain from https://console.x.ai/. |
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
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| grokA | Ask Grok AI to analyze X/Twitter links, search X, or answer questions. Defaults to free browser mode; auto-switches to API for structured output. |
| grok_budgetB | View or adjust Grok API budget. Check spending, remaining balance, or modify limits. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools have completely distinct purposes: 'grok' handles AI analysis and search operations, while 'grok_budget' manages API budget and spending. There is no overlap in functionality, making it impossible to confuse them.
Both tools follow a consistent naming pattern with the 'grok' prefix and descriptive suffixes ('grok' and 'grok_budget'), using snake_case consistently. This creates a predictable and readable naming scheme.
With only two tools, the server feels severely under-scoped for a Grok AI integration. Key operations like managing conversation history, configuring modes, or handling errors are missing, making the set too thin for practical agent use.
The toolset is highly incomplete for an AI assistant domain. It lacks core functionalities such as conversation management, response customization, error handling, or user preference settings, leaving significant gaps that will hinder agent workflows.