"A system for task management and integration with AI editors using multiple LLMs" matching MCP servers:

Enables integration with financial transaction data through REST APIs, PostgreSQL databases, and document storage systems. Demonstrates agentic AI capabilities by connecting to Alpha Vantage API and managing financial data through natural language interactions.

About Your task manager is the best agent memory you're not using. An agent-native context layer over your existing task app.

An MCP server that exposes the llms.txt file and its referenced local or external resources from a project root to provide context for AI models. It automatically parses documentation links and URLs to make them accessible as additional MCP resources.

he Maximo MCP Server bridges AI agents (Claude, Cursor, Antigravity) with your IBM Maximo environment. It empowers your AI to autonomously discover Object Structures (APIs), inspect schemas, and query live data via OSLC. Instead of hallucinating field names, the AI validates queries instantly and ca

Enables agents to discover the llms.txt index covering any site, fetch its linked documentation pages as markdown, and search across parsed indexes by section heading, link title, and notes.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Async MCP server for running long-running AI tasks with real-time progress monitoring, enabling users to start, monitor, and manage complex AI workflows across multiple models.

Enables fast, token-efficient access to large documentation files in llms.txt format through semantic search. Solves token limit issues by searching first and retrieving only relevant sections instead of dumping entire documentation.

Provides AI clients with a persistent, readable and writable long-term memory layer over MCP, enabling creation, retrieval, tagging, updating, and deletion of memories across sessions.

Local-first knowledge system for reasoning agents, exposing facts, evidence, documents, retrieval, and audit history through a thin stdio MCP server.

Production-ready MCP server that integrates OpenAI API with extensible tool support, enabling dynamic plugin loading and knowledge search capabilities through multiple interfaces including CLI and browser UI.

Pre-trade risk validation and position sizing for AI trading agents via G-formula and Iron Fist.

Enables chat with multiple LLM providers (OpenAI and Anthropic) while maintaining persistent conversation memory. Provides extensible tool framework for various operations including echo functionality and conversation storage/retrieval.

A Model Context Protocol server that enables LLMs to interact directly with MongoDB databases, allowing users to query collections, inspect schemas, and manage data through natural language.

MCP server for NodeBB forums that enables AI assistants to access forum data, search topics, and perform semantic search via the Model Context Protocol.

A multi-tool AI assistant system that uses Model Context Protocol to connect language models with various tools, including math calculations and weather information.

MCP server for a modular RAG system that enables natural language question answering over enterprise documents with intent-aware routing, adaptive retrieval, and citation-backed responses.

Provides file system access for resume matching through JSON-RPC, enabling semantic search and workflow orchestration with LangGraph.

Implements a Model Control Protocol server integrated with Google Gemini LLM, providing a flexible framework for building AI-powered applications.

Improves AI agent task performance by providing task area segmentation, hierarchical RAG, and hybrid search capabilities.