"A service or tool named 'imageFX'" matching MCP servers:

A persistent 24/7 background daemon that aggregates all downstream MCP servers into one unified connection and layers on a real-time notification gateway so AI agents can receive events from X/Twitter, Slack, Email, and webhooks.

MCP server that routes natural language requests to structured tool calls using a LoRA-tuned small language model, with built-in validation, retry, and fallback recovery.

A Model Context Protocol service that enables agent authentication and integration with TrustGo platform, providing access to real-time data like price, sigma score, and mindshare bubble analytics.

An MCP proxy that embeds tool definitions and returns only the top-k semantically relevant tools per query, reducing context usage and routing calls to upstream MCP servers.

Central registry for AI tools with vector search and knowledge graph, enabling intelligent tool discovery, chaining, and execution via MCP.

Graph-based tool retrieval for LLM agents. Builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy from 12% to 82% with 79% fewer tokens. Also works as an MCP Proxy to aggregate multiple servers behind 3 meta-tools.

A single MCP server that provides dynamic access to thousands of APIs through discovery and proxy, eliminating the need to install and configure multiple separate MCP servers.

Enables AI agents to securely discover, invoke, and manage tools through a hardened MCP endpoint with protections like injection detection, circuit breakers, retry backoff, response caching, context-window limiting, and state snapshots.

Analyzes multi-step AI agent tool chains to compute success probability, identify bottlenecks, and suggest better execution orders, enabling more reliable agents via local pure-math computation.

A generic MCP proxy that filters which tools are exposed from a remote MCP server, reducing context window token usage by only loading the tools you actually need.

A configurable MCP gateway that runs multiple Streamable HTTP MCP servers and exposes all their tools through a single endpoint, enabling tool aggregation and routing for MCP clients.

Reference implementation of a Model Context Protocol server for integrating external APIs as agent tools. Includes built-in tools for weather, database queries, web search, and calculations, with authentication, rate limiting, and logging.

Enables agents to discover and invoke travel recommendations with partner-specific caps and exclusions via MCP JSON-RPC.

A framework for building hot-loadable MCP tools that feature conversational negotiation, graduated permissions, and zero-downtime updates. It enables persistent state continuity across server restarts and provides a hypothetical evaluation system for tool actions.

A service for managing ESP8266/NodeMCU IoT devices that provides both REST/WebSocket APIs and implements the Model Context Protocol for AI assistant integration.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

A standalone MCP gateway/proxy server that lets any MCP-compatible client search and call tools across multiple downstream MCP servers through a single mcp proxy tool.

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

Enables AI agents to discover and execute tools via a secure MCP server with JWT authentication, RBAC, rate limiting, and audit logging.

An interface enabling high-frequency communication between AI tools (like Cursor and Windsurf) and users, allowing for option selection and information gathering through CLI, Web, or PyQt interfaces.