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Products that do what An MCP server that gives LLMs temporal awareness and time calculation does

This is an open‑source Model Context Protocol (MCP) server that gives any LLM a sense of the passage of time. Most MCP demos wire LLMs to external data stores. That’s useful, but MCP is also a chance to give models perception — extra senses beyond the prompt text. Six functions (`current_datetime`, `time_difference`, `timestamp_context`, etc.) give Claude&#x2F;GPT real temporal awareness: It can spot pauses, reason about rhythms, and even label a chat’s “three‑act structure”. Runs locally in <60 s (Python) or via a hosted demo. If time works, what else could we surface? - Location &#x2F;…

  1. 1

    Memory for your AI Tools

    2025

  2. 2OS

    Large Language Models (LLMs) are powerful, but they’re limited by fixed context windows and outdated knowledge. What if your AI could access live search, structured data extraction, OCR, and more—all through a standardized interface? We built the JigsawStack MCP Server, an open-source implementation of the Model Context Protocol (MCP) that lets any AI model call external tools effortlessly. Here’s what it unlocks: - Web Search & Scraping: Fetch live information and extract structured data from web pages. - OCR & Structured Data Extraction: Process images, receipts, invoices, and handwritten…

    2025

  3. 3CR

    Hey HN, I built pg-mcp, a Model Context Protocol (MCP) server for PostgreSQL that provides structured schema inspection and query execution for LLMs and agents. It's multi-tenant and runs over HTTP&#x2F;SSE (not stdio) Features - Supports multiple database connections from multiple agents - Schema Introspection: Returns table structures, types, indexes and constraints; enriched with descriptions from pg_catalog. (for well documented databases) - Read-Only Queries: Controlled execution of queries via MCP. - EXPLAIN Tool: Helps smart agents optimize queries before execution. - Extension…

    2025 · github.com

  4. 4

    Your memories, in every LLM you use.

    2025

  5. 5RM

    We’ve open-sourced the Robot MCP Server, a tool that lets large language models (LLMs) talk directly to robots running ROS1 or ROS2. What it does - Connects any LLM to existing ROS robots via the Model Context Protocol (MCP) - Natural language → ROS topics, services, and actions (And the ability to read any of them back) - Works without changing robot source code Why it matters - Makes robots accessible from natural language interfaces - Opens the door to rapid prototyping of AI-robot applications - We are trying to create a common interface for safe AI ↔ robot communication This is too big…

    Sep 2025 · github.com

  6. 6MS

    Hi HN! I built a custom MCP (Model Context Protocol) server that connects Blender to LLMs like ChatGPT, Claude, and any other llm supporting tool calling and mcps, enabling the AI to understand and control 3D scenes using natural language. You can describe an entire environment like: > “Create a small village with 5 huts arranged around a central bonfire, add a river flowing on the left, place a wooden bridge across it, and scatter trees randomly.” And the system parses that, reasons about the scene, and builds it inside Blender — no manual modeling or scripting needed. What it can do: -…

    2025 · blender-mcp-psi.vercel.app

  7. 7AM
  8. 8

    Chat with your business data inside Claude, ChatGPT and more

    Jun 2026 · databox.com

  9. 9

    Persistent AI memory across Claude Desktop & Cursor IDE

    Oct 2025

  10. 10CM

    Every MCP tool call dumps raw data into Claude Code's 200K context window. A Playwright snapshot costs 56 KB, 20 GitHub issues cost 59 KB. After 30 minutes, 40% of your context is gone. I built an MCP server that sits between Claude Code and these outputs. It processes them in sandboxes and only returns summaries. 315 KB becomes 5.4 KB. It supports 10 language runtimes, SQLite FTS5 with BM25 ranking for search, and batch execution. Session time before slowdown goes from ~30 min to ~3 hours. MIT licensed, single command install: &#x2F;plugin marketplace add mksglu&#x2F;claude-context-mode…

    Feb 2026 · github.com

  11. 11

    An OKF-backed Model Context Protocol (MCP) server delivering persistent long-term memory and SQLite FTS5 search for AI agents. - fellowgeek/mcp-memory

    24d ago · github.com

  12. 12

    Allow AI Agents to help you with Figma designs!

    Jan 2026

  13. 13WM

    Hi HN – I built an open-source, self-hosted Model Context Protocol (MCP) server for WhatsApp: https:&#x2F;&#x2F;github.com&#x2F;lharries&#x2F;whatsapp-mcp It connects to your personal WhatsApp account via the WhatsApp Web multi-device API (using whatsmeow from the Beeper team), and doesn't rely on third-party APIs. All messages are stored locally in SQLite. Nothing is sent to the cloud unless you explicitly allow your LLM to access the data via tools – so you maintain full control and privacy. The MCP server can: - Search your messages, contacts, and groups - Send WhatsApp messages to…

    2025 · github.com

  14. 14

    Free MCP for security AI: live BGP, DNS, threat graph

    May 2026 · whisper.security

  15. 15
    Click133

    Live research context for ChatGPT and Claude

    25d ago · useclick.ai

  16. 16SM

    Jul 2026 · uml.gpmai.workers.dev

  17. 17ST

    Hi! After learning about MCP, I'm really excited about the future of provider-agnostic, re-usable tooling. Unfortunately I've found that while it's easy to implement an MCP server for use with tools that support it (such as Claude Desktop), it's not as easy to implement your own support (such as integrating an MCP server into your own LLM application). We implemented a thin MCP wrapper that easily integrates with Mirascope calls so that you can hook up an MCP server and client super easily to any supported LLM provider. Excited to see what people build with this!

    2025 · mirascope.com

  18. 18GL

    Hey HN! We're Paul, Preston, and Daniel from Zep. We've just open-sourced Graphiti, a Python library for building temporal Knowledge Graphs using LLMs. Graphiti helps you create and query graphs that evolve over time. Knowledge Graphs have been explored extensively for information retrieval. What makes Graphiti unique is its ability to build a knowledge graph while handling changing relationships and maintaining historical context. At Zep, we build a memory layer for LLM applications. Developers use Zep to recall relevant user information from past conversations without including the entire…

    2024 · github.com

  19. 19

    Your context, available to every agent.

    Jul 2026 · in-parallel.com

  20. 20
    N8N2MCP137

    Turn your N8N workflow to MCP servers with just 3 clicks

    2025

  21. 21MA

    Hey HN, I spent my xmas break building an agent framework called mcp-agent [1](https:&#x2F;&#x2F;github.com&#x2F;lastmile-ai&#x2F;mcp-agent) for Model Context Protocol [2]. It makes it easy to build AI apps with MCP servers, and implements every pattern from the popular Building Effective Agents blog [3] as well as OpenAI’s Swarm [4]. I’m sharing it early to get community feedback on where to take it from here, and to ask for contributions. For those who aren’t familiar with MCP, I think of it as a standardized interface to let AI communicate with software via tool calls, resources and…

    2025 · github.com

  22. 22CI

    Hi, I'm Daniel from Zep. I've integrated the Cursor IDE with Graphiti, our open-source temporal knowledge graph framework, to provide Cursor with persistent memory across sessions. The goal was simple: help Cursor remember your coding preferences, standards, and project specs, so you don't have to constantly remind it. Before this integration, Cursor (an AI-assisted IDE many of us already use daily) lacked a robust way to persist user context. To solve this, I used Graphiti’s Model Context Protocol (MCP) server, which allows structured data exchange between the IDE and Graphiti's temporal…

    2025

  23. 23RA

    Hey HN! A few months ago we shared mcp-agent (https:&#x2F;&#x2F;github.com&#x2F;lastmile-ai&#x2F;mcp-agent) [1][2], a lightweight framework that implements every agent pattern from Anthropic’s Building Effective Agents blog [3] and handles MCP server&#x2F;client management seamlessly. Our core bet is that connecting LLMs to tools, resources, and external systems will soon be MCP-native by default. Today we're launching a significant update: Agents as MCP servers. Currently "agentic" behavior exists only on the MCP client side – clients like Claude or Cursor use MCP servers to solve tasks.…

    2025 · github.com

  24. 24MK

    I built a Model Context Protocol server that allows users to interact with Kafka using natural language instead of complex CLIs. It uses LLMs to interpret commands in plain English and executes the corresponding Kafka operations. This makes Kafka more accessible to non-experts while maintaining its powerful functionality.

    2025 · github.com

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