Agent Aggregator
Related Servers
Alternatives to Agent Aggregator
No user-submitted related servers found.
Related Servers
AlicenseAqualityCmaintenanceAggregates multiple MCP servers into a single interface, reducing token overhead and simplifying tool management for LLMs.629 npm18Apache 2.0- FlicenseNot gradedqualityAmaintenanceAn MCP server that aggregates, manages, and proxies other MCP servers, enabling LLMs to discover, add, configure, enable/disable, and use tools from multiple servers dynamically.-
- FlicenseNot gradedqualityDmaintenanceAggregates multiple MCP servers and custom Python tools behind a single endpoint, with intelligent context and tool discovery for AI agents.-
- FlicenseNot gradedqualityAmaintenanceEnables LLMs to dynamically search for, add, configure, enable/disable, and aggregate tools from multiple MCP servers at runtime, with persistent configuration and proxying.-
- FlicenseNot gradedqualityAmaintenanceEnables LLMs to manage and proxy multiple MCP servers, dynamically extending capabilities by adding, configuring, enabling, disabling, and aggregating their tools through a unified interface.-
- FlicenseNot gradedqualityAmaintenanceEnables LLMs and clients to discover, add, configure, enable or disable, and aggregate tools from multiple MCP servers under unified prefixes. It also proxies other MCP servers and persists configurations across sessions.-
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.