AI · alternatives · 2026
24 alternatives to Explorium MCP
Integrate B2B data to any LLM in minutes
Explorium MCP is a tool that connects B2B company and contact data to large language models through a Model Context Protocol integration. It enables AI agents, applications, and workflows to access live business… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
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Connect direct to Salesforce & HubSpot with native formulas
2025 · coefficient.io · its alternatives →
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Power your AI agents with enterprise-ready tools via MCP
2025 · merge.dev · its alternatives →
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I'm Mike, Head of Eng/Product at Alloy Automation. We built MCP by Alloy Automation to give your AI agents structured access to business-critical systems without the integration headache. We've built MCP servers covering thousands of tools across platforms like Quickbooks, Xero, Notion, HubSpot, and Salesforce. Pick the tools you need, provision a server, and ship faster. Need more control? Our Connectivity API gives you programmatic access to all the same tools for custom integrations beyond MCP. Everything runs with scoped auth utilizing our battle-tested credential management system…
2025 · ai.runalloy.com · its alternatives →
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OpenMemory MCP▲379Sync memory across AI's so they pick up where you left off.
2025 · mem0.ai · its alternatives →
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Pipedream MCP▲2912,500+ APIs and 10,000+ tools for your AI assistant
2025 · mcp.pipedream.com · its alternatives →
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SchemaFlow▲128Real-time database schemas for AI-IDEs via MCP protocol
2025 · schemaflow.dev · its alternatives →
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Connect any API to any AI agent
May 2026 · mcp-bridge.ai · its alternatives →
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Skip migration and launch MCP with built-in Auth
Nov 2025 · arcade.dev · its alternatives →
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Hey HN, I spent my xmas break building an agent framework called mcp-agent [1](https://github.com/lastmile-ai/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 · its alternatives →
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Air MCP▲129Tool For All AI Integrations, let AI use your apps
2025 · air-mcp.com · its alternatives →
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Let your AI agents trigger communication without any code
2025 · exotel.com · its alternatives →
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Global APIs as MCP powered by AI Gateway
2025 · mcp.higress.ai · its alternatives →
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I've been working with the Featureform team on their new open-source project, [EnrichMCP][1], a Python ORM framework that helps AI agents understand and interact with your data in a structured, semantic way. EnrichMCP is built on top of [MCP][2] and acts like an ORM, but for agents instead of humans. You define your data model using SQLAlchemy, APIs, or custom logic, and EnrichMCP turns it into a type-safe, introspectable interface that agents can discover, traverse, and invoke. It auto-generates tools from your models, validates all I/O with Pydantic, handles relationships, and…
2025 · github.com · its alternatives →
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2025 · npmjs.com · its alternatives →
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Peliqan▲110Connect Claude to 250+ SaaS apps via one MCP server
2024 · peliqan.io · its alternatives →
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Hey HN, I’m Austin, founder of Salestrics (salestrics.com). The Problem: > Most AI agents today are trapped in chat windows. While models are smart enough to run complex multi-step workflows, giving them production access to business context (CRM, support, billing) usually means managing unsafe local API keys or hacking together fragile point-solution scripts. What We Built: We built Salestrics to serve as both an all-in-one revenue workspace (CRM, service desk, billing, docs, email) and a production-grade Model Context Protocol (MCP) execution proxy. How It Works: Unified Context: Instead…
Aug 2026 · salestrics.com · its alternatives →
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MCP360▲61Hey HN Community, I built MCP360 after spending weeks integrating APIs for an AI agent project. Each tool needed its own setup, auth, billing, and maintenance. When any APIs changed, my integrations broke. I got tired of it. MCP360 is a single gateway giving AI agents access to 100+ tools through one config block. Search engines, web scraping, SEO, e-commerce data, maps, domain tools, and more. Real example: Instead of managing Google Search, web scraping, SERP tracking, and keyword research as 4 separate subscriptions (4 bills, 4 auth systems, 4 points of failure), you connect once. Works…
2025 · mcp360.ai · its alternatives →
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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/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 /…
2025 · github.com · its alternatives →
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Docs2mcp▲29Turn any API documentation into a simple hosted MCP server.
2025 · docs2mcp.com · its alternatives →
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Hey HN! We're Wen and Tobias, and we're building Metorial (https://metorial.com), an integration platform that connects AI agents to external tools and data using MCP. The Problem: While MCP works great locally (e.g., Cursor or Claude Desktop), server-side deployments are painful. Running MCP servers means managing Docker configs, per-user OAuth flows, scaling concurrent sessions, and building observability from scratch. This infrastructure work turns simple integrations into weeks of setup. Metorial handles all of this automatically. We maintain an open catalog of ~600 MCP servers…
2025 · github.com · its alternatives →
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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 · its alternatives →
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Hey all! I recently gave a workshop talk at PyCon Greece 2025 about building production-ready agent systems. To check the workshop, I put together a demo repo: (I will add the slides too soon in my blog: https://www.petrostechchronicles.com/) https://github.com/Aherontas/Pycon_Greece_2025_Presentation_... The idea was to show how multiple AI agents can collaborate using FastAPI + Pydantic-AI, with protocols like MCP (Model Context Protocol) and A2A (Agent-to-Agent) for safe communication and orchestration. Features: - Multiple agents running in containers -…
2025 · github.com · its alternatives →
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Hey HN, Sagiv from liblab is here. We've been deep in the world of API tooling for years at liblab, primarily focusing on generating SDKs and documentation from OpenAPI specs. Recently, we kept running into a recurring frustration: connecting AI tools to existing APIs is way more complex than it should be. You start with a simple goal – let an LLM talk to your API – and suddenly you're neck-deep in spinning up infrastructure, wrestling with authentication, and writing a ton of custom glue code just to translate natural language into structured API calls. Then you have to maintain it all. To…
2025 · mcp.liblab.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →