The open standard turning a fragmented AI integration landscape into a coherent, vendor-neutral ecosystem.
The Model Context Protocol is an open standard introduced by Anthropic in November 2024 for connecting AI models to the tools, data sources, and services they need to operate in production environments.
Before MCP, every integration between a language model and an external system required custom engineering work. Each tool needed its own connector. Teams shipping AI features spent more time on plumbing than on the features themselves. Anthropic described this as the N×M integration problem: ten applications connecting to one hundred tools required up to one thousand custom integrations.
MCP solves this by defining a single, standardized interface through which any AI model can communicate with any compatible service. A tool built once for MCP works across every model and platform that supports the protocol.
The shift to MCP is widely viewed as one of the most consequential architectural changes in applied AI since the arrival of large language models themselves.
Universal standard
One interface connects any AI model to any compatible service - no custom connectors, no per-tool maintenance.
Linear scaling
Integration effort no longer grows quadratically. Ten apps, one hundred tools - no longer one thousand custom integrations.
Ecosystem coherence
Compared to HTTP for the web and USB-C for hardware - MCP turns a fragmented landscape into coherent infrastructure.
Vendor-neutral
Governed under the Linux Foundation with backing from Google, Microsoft, AWS, Cloudflare, and Bloomberg.
Production-ready
Already deployed across hundreds of Fortune 500 companies within twelve months of launch.
Industry consensus
Anthropic, OpenAI, Google, Microsoft, and GitHub - the full stack behind a single open standard.
Within twelve months, MCP grew from a launch announcement to the fastest-adopted AI infrastructure standard in history. Boston Consulting Group described it as “a deceptively simple idea with outsized implications.”
Jensen Huang of NVIDIA stated in late 2025 that the work on MCP has completely revolutionized the AI landscape. Integration complexity for enterprise AI now rises linearly rather than quadratically.
MCP launched by Anthropic
Open standard introduced for connecting AI models to tools, data sources, and services.
OpenAI commits
OpenAI announced full MCP support across its products.
Microsoft & GitHub join
Both joined the protocol steering committee at Build 2025.
Google DeepMind follows
Google DeepMind adopted MCP, cementing cross-industry consensus.
Linux Foundation governance
Anthropic donated MCP to the Agentic AI Foundation - vendor-neutral, open infrastructure.
Every AI application built on MCP needs services to call. The companies building those services are positioned to capture a structural share of the AI infrastructure stack.
Each tool in the SOMA marketplace is exposed as a fully MCP-compatible service, accessible to any model or agent through the standard protocol. The first tool, SOMARIZER, delivers context compression. Additional tools targeting other layers of the AI infrastructure stack are in active development.
As MCP adoption continues to accelerate, the demand for high-quality services running behind the protocol grows with it. SOMA is designed to meet that demand from the start - with an architecture that produces continuously improving services and a platform engineered to scale across multiple categories of infrastructure.
MCP-native from day one
Every SOMA service exposes a standard MCP interface. No custom connectors. No per-model configuration.
Open competition
Each service operates as a competition between independent providers. The best implementation always wins and is served automatically.
A platform built to scale
SOMARIZER is the first service. More tools targeting distinct layers of AI infrastructure are in active development.
SOMA is a marketplace for MCP (Model Context Protocol) services, built for AI agents that need to integrate, coordinate, and execute reliably at scale. The first service live on SOMA is Somarizer, with more MCP services in the pipeline.
MCP stands for Model Context Protocol, an open standard for connecting AI models with external tools, data sources, and execution environments. It gives AI agents a consistent way to exchange context and take action across different systems. SOMA delivers MCP services as a continuously optimized layer, so teams plug in performance instead of building it from scratch.
Context Compression is the process of reducing the number of tokens an AI model needs to produce a given output, while preserving the quality of that output. Fewer tokens translate directly into lower costs, faster responses, and more usable space inside any context window. For production AI workloads, the savings compound with every request.
Right now, SOMA has one live tool: SOMARIZER - a context compression service for AI agents and LLM applications. It plugs into existing pipelines and shrinks input tokens without compromising downstream task performance. More tools are in the works and coming soon.