What AI models does the agent use?

The agent has access to Claude, DeepSeek, Gemini, and other top models. It automatically routes to the best model for each task — you never have to think about API keys or token limits.

Yes. Each agent runs in an isolated environment. We don't train on your data, and you can export or delete everything at any time. The underlying engine (GoGogot) is open-source, so you can audit exactly how it works.

What can the agent actually do?

Browse the web, process files (CSV, PDF, images), run scheduled tasks, remember context across sessions, and communicate via Telegram or Slack. Think of it as a capable junior employee, not a chatbot.

How does memory work?

The agent maintains persistent memory across sessions. It remembers your preferences, past conversations, and task context. You can also explicitly tell it to remember or forget things.

Can I self-host the agent?

Absolutely. GoGogot is 100% open-source. Run it on your own hardware for free. cowork.ink is the managed version — we handle servers, model costs, updates, and uptime so you don't have to.

Is there a free trial?

We offer a 7-day money-back guarantee. Spin up an agent, give it real tasks, and if it doesn't save you time, we'll refund you — no questions asked.

What is Model Context Protocol (MCP)?

Model Context Protocol (MCP) is an open standard created by Anthropic in November 2024 that defines how AI applications connect to external tools, data sources, and services. It is built on JSON-RPC 2.0 and follows a three-tier architecture of hosts, clients, and servers. Every major AI platform — including OpenAI, Google, and Microsoft — adopted it within six months of launch. MCP is now governed by the Linux Foundation's Agentic AI Foundation.

What is the difference between MCP and function calling?

Function calling is how an LLM expresses *intent* to use a tool — it generates a structured JSON instruction. MCP is the infrastructure that handles *how* tools are discovered and executed across different AI systems. They are complementary: function calling is the instruction, MCP is the universal socket it plugs into. MCP adds dynamic tool discovery, stateful sessions, and portability that raw function calling lacks.

What are the three types of MCP primitives?

MCP defines five primitives: three server-side (Tools for executing actions, Resources for read-only context, and Prompts for reusable templates) and two client-side (Sampling lets servers request LLM completions, and Elicitation lets servers ask users for input mid-operation). Most MCP servers implement Tools and Resources; Sampling and Elicitation are used in advanced agentic workflows.

MCP introduces real security risks that practitioners must understand. The primary threats are prompt injection (malicious data in tool responses hijacking AI behavior), tool poisoning (hidden instructions in tool descriptions), and rug pull attacks (server changing tool behavior after gaining trust). Best practices include running MCP servers in sandboxed environments, auditing server code before use, and only connecting to servers from trusted sources. See our [MCP security guide](/blog/mcp-security-best-practices/) for full coverage.

How many MCP servers are there?

As of early 2026, there are 6,400+ servers in the official MCP Registry, with an estimated 16,000+ unique MCP servers across the web. Categories span development tools, databases, cloud platforms, productivity apps, search, and more. The official registry at modelcontextprotocol.io/registry is the best starting point for finding verified servers.

Model Context Protocol (MCP): The Complete Guide for 2026

COMPLETE guide to Model Context Protocol (MCP) — architecture, primitives, security, 6,400+ servers, and the 2026 roadmap. The USB-C port for AI, explained.

Frequently Asked Questions

What is Model Context Protocol (MCP)?: Model Context Protocol (MCP) is an open standard created by Anthropic in November 2024 that defines how AI applications connect to external tools, data sources, and services. It is built on JSON-RPC 2.0 and follows a three-tier architecture of hosts, clients, and servers. Every major AI platform — including OpenAI, Google, and Microsoft — adopted it within six months of launch. MCP is now governed by the Linux Foundation's Agentic AI Foundation.
What is the difference between MCP and function calling?: Function calling is how an LLM expresses *intent* to use a tool — it generates a structured JSON instruction. MCP is the infrastructure that handles *how* tools are discovered and executed across different AI systems. They are complementary: function calling is the instruction, MCP is the universal socket it plugs into. MCP adds dynamic tool discovery, stateful sessions, and portability that raw function calling lacks.
What are the three types of MCP primitives?: MCP defines five primitives: three server-side (Tools for executing actions, Resources for read-only context, and Prompts for reusable templates) and two client-side (Sampling lets servers request LLM completions, and Elicitation lets servers ask users for input mid-operation). Most MCP servers implement Tools and Resources; Sampling and Elicitation are used in advanced agentic workflows.
Is MCP secure?: MCP introduces real security risks that practitioners must understand. The primary threats are prompt injection (malicious data in tool responses hijacking AI behavior), tool poisoning (hidden instructions in tool descriptions), and rug pull attacks (server changing tool behavior after gaining trust). Best practices include running MCP servers in sandboxed environments, auditing server code before use, and only connecting to servers from trusted sources. See our [MCP security guide](/blog/mcp-security-best-practices/) for full coverage.
How many MCP servers are there?: As of early 2026, there are 6,400+ servers in the official MCP Registry, with an estimated 16,000+ unique MCP servers across the web. Categories span development tools, databases, cloud platforms, productivity apps, search, and more. The official registry at modelcontextprotocol.io/registry is the best starting point for finding verified servers.