10k+active public MCP servers in the ecosystem in the first year after release

97MSDK downloads per month (Python + TypeScript)

714→16kgrowth in the number of MCP servers from January 2025 to 2026

1200+Quantium employees work with data through MCP agents

Industry solutions

What you can build with MCP

E-commerce and retail Connect the agent to PIM, warehouse and orders via MCP servers Answers on availability, prices and order statuses from live data instead of manual exportsLearn more →Manufacturing Wrap MES, ERP and technical documentation into MCP servers for agents Engineers and operators get answers on procedures and line status without searching across systemsLearn more →Finance and banking Give agents governed access to transactions and compliance data via MCP Risk scoring, fraud detection and compliance monitoring in real timeLearn more →Logistics Connect TMS, tracking and document workflow as MCP tools The agent builds delivery statuses and produces documents across the end-to-end processLearn more →B2B distribution Connect CRM, price lists and a customer's order history through a single MCP layer The manager and agent prepare proposals and upsells on the full customer contextLearn more →IT and development Connect Git, trackers and CI/CD to the agent via MCP The agent finds context across code and tasks, speeding up development and onboardingLearn more →Professional services Deploy Sloy as an MCP server for corporate memory across projects and people Decisions and project history are available to agents as verifiable memory; knowledge is not lost during staff rotationLearn more →Real estate Wrap asset databases, CRM and documents into MCP servers The agent selects assets and prepares documents from up-to-date portfolio dataLearn more →

Capabilities

MCP capabilities

Sources: CRM, Git, BI, files, email, tasks, financeMCP servers (unified interface + OAuth 2.1)Sloy — an MCP server for corporate memoryMCP protocol (two-way)AI agent / client: Claude, ChatGPT, Gemini, CopilotActions in systems + verifiable answers

On the left are enterprise data sources and tools. Each is wrapped in an MCP server with a unified interface and authorization. On the right, the AI agent (any client: Claude/ChatGPT/Gemini/Copilot) connects to servers through the MCP protocol, reads data, and performs actions. Sloy connects as an MCP server for enterprise memory. The arrows are bidirectional: context reads and action execution.

One protocol instead of N×M integrations

A data source is connected once and works with all agents — integration cost and time drop, and one-off connectors stop multiplying.

Transferable integrations

MCP servers outlive a change of LLM, team or contractor: nothing is rewritten from scratch when a project is handed over.

Access to up-to-date enterprise data

The agent answers from live data in CRM, Git, BI and files instead of a stale training corpus — fewer hallucinations and manual checks.

Managed access and audit

OAuth 2.1, centralized authorization and call logging give security teams control over what the agent can access.

Two-way tools, not read-only

The agent not only reads data but also performs actions (create a task, update a record) — automating end-to-end processes, not just prompts.

Compatible with any client

One MCP server serves Claude, ChatGPT, Gemini, Cursor and Copilot — the company isn't locked into a single vendor.

Dynamic tool loading

The agent picks the right tools on the fly instead of hardcoded integrations — new scenarios launch without rewriting code.

Integration with Sloy corporate memory

The company's work trail (chats, meetings, Git, finance) is served to agents as verifiable memory via MCP — decisions are made on company context.

Mature international standard

MCP has been handed over to the Agentic AI Foundation (Linux Foundation) and is supported by OpenAI, Google, Microsoft, and AWS, betting on a standard rather than custom-built code.

Approach

How we implement MCP

Without modifying the core

We don't fork or patch the MCP core. MCP stays on the standard, updatable version — we move business logic into separate microservices alongside it, so platform updates don't break your customizations.

International Standards, Not Homegrown Hacks

Where a mature international solution exists, we use it instead of inventing our own protocol or platform. Before writing code, we study how the problem is already solved in the industry.

Transferability

The solution is loosely coupled and documented: it can be handed over between teams and contractors without rewriting. You are not tied to us.

AI compatibility

MCP in the AI stack

Open standard under the Linux Foundation

Anthropic transferred MCP to the Agentic AI Foundation; founding members include Block, OpenAI, AWS, Google, and Microsoft. This is not a vendor protocol, but community-driven infrastructure.

Native support in major clients

Claude, ChatGPT, Gemini, Microsoft Copilot, Cursor and VS Code have first-class MCP integration — one server works with all of them.

Adopted by major platforms

OpenAI (Agents SDK, Responses API, March 2025), Google DeepMind (Gemini, April 2025), Microsoft Azure AI Agent Service, AWS, Cloudflare, Bloomberg, Snowflake, Salesforce.

MCP in RFPs as a baseline requirement

By the end of 2025, MCP support moved from a competitive edge to a mandatory line in enterprise procurement requirements — plan for compatibility in advance.

Mature security mechanisms

OAuth 2.1 and centralized governance handle authorization; MCP servers also require supply chain control, and KT.Team connects sources through managed servers.

News

What's new in MCP

All news

2026-08-22
Roadmap updated: agent identity, unified HTTP transport, SDK experience
The March roadmap has been expanded from 4 to 5 priorities. Agent identity and SDK developer experience have been added as a separate item; messaging primitives (Tasks, subscriptions/listen, progress) are being extended to server-initiated events via webhooks/channels instead of polling, and the local stdio transport is proposed to be unified with remote HTTP. The release follows the 2026-07-28 specification, the largest revision since the protocol launched.

MCP's move from polling to server-initiated events via webhooks/channels is a pattern that message brokers like Kafka addressed with push subscriptions years ago. Apache Kafka →Agent identity as a separate MCP priority for 2026 is not new - in enterprise LLM-gateway products, agent access control is already standard functionality. LLM & Security Gateway →
2026-07-28
Specification dated July 28, 2026: the protocol becomes stateless
The largest revision since launch. Protocol-level sessions (Mcp-Session-Id), the initialize/notifications/initialized handshake, ping, and SSE resumability were removed; cross-call state is now carried in explicit handle arguments. server/discover was added, the MRTR pattern replaced server-initiated requests, and resultType became mandatory. Roots, Sampling, Logging, and the HTTP+SSE transport are marked Deprecated (at least 12 months before removal), and Dynamic Client Registration gives way to Client ID Metadata Documents.

MCP gives up persistent sessions and subscriptions for scalability over plain HTTP, while Kafka solves the same horizontal scaling problem through partitioning, not through protocol statelessness Apache Kafka →
2026-01-26
MCP Apps: interactive UI inside chat, the first official extension
MCP server tools can return interactive HTML components, such as dashboards, forms, and multi-step wizards, rendered in an iframe sandbox directly in the chat with the model. The first extension to move from an SEP proposal (November 21, 2025) to official production-ready status.

MCP Apps directly builds on the OpenAI Apps SDK pattern and the earlier MCP-UI project OpenAI →n8n has provided a visual UI over workflow nodes for years; MCP Apps brings a comparable interactive UI into the tool-calling protocol itself for the first time n8n →
2025-11-25
Specification dated November 25, 2025: Tasks, simplified authorization, sampling with tool calling
Protocol anniversary. Experimental task-based workflows were added (SEP-1686, statuses working/input_required/completed/failed/cancelled), Dynamic Client Registration was replaced by URL-based Client ID Metadata Documents (SEP-991), URL mode elicitation for OAuth was added without passing credentials through the client (SEP-1036), tool calling inside sampling requests was added (SEP-1577), and the tool name format was standardized (SEP-986).

LLM & Security Gateway →