"Combining MCP Server Aggregator" matching MCP servers:

Aggregates multiple MCP servers into a single Streamable HTTP endpoint, compressing tools to manage registration limits.

MCP aggregator with many existing NCP templates and allows running external MCP servers too

An MCP aggregator that consolidates multiple MCP servers behind a single interface with just 3 tools (search, get details, execute), reducing context pollution for AI agents by avoiding direct exposure of numerous tool schemas.

Aggregates multiple separate MCP services into a unified SSE endpoint with intelligent tool-name routing, on-demand wake-up, and idle scale-to-zero process shutdown. It also exposes per-service endpoints and caches tool schemas for sub-millisecond discovery.

A distributed MCP server architecture with a master aggregator that orchestrates multiple specialized MCP servers (greeting, math operations, text manipulation) through HTTP transport and JSON-RPC 2.0.

A minimal MCP server with sample tools, resources, and prompts, plus an aggregator to connect multiple external MCP servers and REST APIs, including experimental OAuth support.

A simple aggregator server that allows batching multiple MCP tool calls into a single request, reducing token usage and network overhead for AI agents.

Aziel Runtime is a node-meshed MCP software orchestration suite for digital forensics, auditing, provenance, research, intelligence-support, and secure agent workflows, with a single gated execution path, compartmentalized engines, verifiable receipts, temporal integrity, and explicit capability refusal. It is not merely an API aggregator or generic tool router.

A universal MCP aggregator toolkit that connects AI agents to multiple MCP servers through a single unified configuration. Features ready-made templates, cross-repo prompt workflows, and an npm package for zero-config installation.

Provides fresh project context to coding agents by combining Markdown documentation and live Git state, enabling deterministic startup briefs and bounded document retrieval for MCP-compatible tools.

Provides AI agents with local-first access to Collibra developer documentation via MCP, combining deterministic filesystem search with semantic RAG retrieval.

Aggregator MCP proxy that collapses N downstream MCP servers into 4 meta-tools with progressive tool discovery, and compresses large tool outputs (HTML→Markdown, JSON summarization) with full-output retrieval via read_more and a per-session token-savings report.

Enables AI assistants to perform comprehensive code reviews of local uncommitted changes by combining git diffs with static analysis from linters like ESLint and TypeScript. Returns structured JSON feedback with findings, suggestions, and quality assessments powered by Google's Gemini CLI.

Enables an AI agent to assess Magento 2 / Adobe Commerce projects for target PHP and Magento version compatibility, custom module quality, and dependency security, combining results into concrete upgrade blockers and plans. It provides tools for project status, package update verdicts, module risk scans, release notes, and upgrade planning.

Local-first, read-only Codex session aggregator that indexes multiple CODEX_HOME directories into a SQLite database and provides MCP tools for cross-project, archival, and sub-agent history queries.

Enables comprehensive Roku automated testing by combining WebDriver for UI state verification and ECP for device control, allowing validation of acceptance criteria through natural language queries.

Enables unified code search and analysis over a monorepo, combining exact, semantic, and call graph queries with indexing, incremental updates, and impact analysis.

A Model Context Protocol implementation that enables LLMs to execute complex, multi-step workflows combining tool usage with cognitive reasoning, providing structured, reusable paths through tasks with advanced control flow.

An MCP server that transforms repositories into queryable knowledge by combining static code analysis with git history tracking. It allows users to investigate codebase structure, identify fragile files based on churn, and receive risk assessments through natural language queries.

Hybrid code quality analysis server combining fast logic-based checks with AI-powered deep analysis, offering tools for summaries, quick wins, and trend tracking.