Consult LLM MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GEMINI_MODE | No | Choose between API or CLI mode for Gemini models (optional). Options: api (default), cli | |
| GEMINI_API_KEY | No | Your Google AI API key (required for Gemini models in API mode) | |
| OPENAI_API_KEY | No | Your OpenAI API key (required for o3) | |
| DEEPSEEK_API_KEY | No | Your DeepSeek API key (required for DeepSeek models) | |
| CONSULT_LLM_DEFAULT_MODEL | No | Override the default model (optional). Options: o3 (default), gemini-2.5-pro, deepseek-reasoner |
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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| consult_llmA | Ask a more powerful AI for help with complex problems. Provide your question in the prompt field and always include relevant code files as context. Be specific about what you want: code implementation, code review, bug analysis, architecture advice, etc. IMPORTANT: Ask neutral, open-ended questions. Avoid suggesting specific solutions or alternatives in your prompt as this can bias the analysis. Instead of "Should I use X or Y approach?", ask "What's the best approach for this problem?" Let the consultant LLM provide unbiased recommendations. |
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 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool has a clearly defined and distinct purpose: consulting a more powerful AI for help with complex problems.
Since there is only one tool, naming consistency is inherently perfect. The tool name 'consult_llm' follows a clear verb_noun pattern, which would be consistent if more tools existed.
A single tool is too few for the apparent scope of consulting an LLM for various tasks like code implementation, review, bug analysis, and architecture advice. This forces all functionality into one tool, which is an extreme mismatch and limits the server's utility.
The tool surface is severely incomplete for the domain of AI consultation. While the single tool covers general consultation, there are significant gaps such as no specialized tools for different consultation types (e.g., code_review, bug_analysis, architecture_advice), leading to potential agent failures due to lack of structured operations.