Agent Aggregator
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| NODE_ENV | No | Node environment (e.g., production) | production |
| OPENROUTER_API_KEY | Yes | Your OpenRouter API key for AI model access |
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 | {} |
| prompts | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| filter__updateC | [Filter Management] Update tool visibility filter - control which tools are visible to AI |
| filter__getA | [Filter Management] Get current tool filter configuration |
| filter__resetA | [Filter Management] Reset tool filter to show all available tools |
| ai-tools__explain_codeB | [AI Code Analysis] Provides detailed explanation of the given code |
| ai-tools__review_codeA | [AI Code Analysis] Reviews the given code for quality and best practices |
| ai-tools__fix_codeC | [AI Code Analysis] Fixes bugs or issues in the given code |
| ai-tools__edit_codeC | [AI Code Analysis] Edits the given code based on instructions |
| ai-tools__test_codeB | [AI Code Analysis] Generates tests for the given code |
| ai-tools__simulate_commandC | [AI Code Analysis] Simulates the execution of a given command |
| ai-tools__analyze_projectB | [AI Code Analysis] Analyzes project structure and provides insights |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| server_concept | Explains the concept and capabilities of the Agent Aggregator MCP server |
| available_servers | Lists all connected MCP servers and their purposes |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 10 tools
The three filter tools are clearly distinct, and the AI code tools have distinct actions (explain, review, fix, edit, test, simulate, analyze). Some overlap exists between fix_code and edit_code, but descriptions clarify the difference.
All tools follow a consistent domain__action pattern using double underscores, but the action part is not uniformly verb_noun (e.g. filter__get vs ai-tools__explain_code). This is a minor inconsistency that does not impede readability.
Ten tools is well-scoped for an aggregator with two functional areas: filter management and AI code analysis. Each tool seems to serve a distinct purpose without redundancy.
Filter management covers get/update/reset completely, and AI code analysis covers explain, review, fix, edit, test, simulate, and project analysis. There are no obvious dead ends or missing core operations for the stated domains.