MCP server
Everything MCP server
The MCP project's Everything server is a test server that shows every protocol feature. For building and testing MCP clients only.
- Official server
- Developer tools
At a glance
- Maintained by
- Model Context Protocol project (Anthropic reference servers)
- Tools exposed
- 10 listed below
- Reviewed
- September 24, 2026
Why it matters
What it does and why it matters
The Everything server exists for developers who build MCP clients or want to learn the protocol. It demonstrates each feature: simple tools, structured content, images, resource links, long-running operations, sampling, elicitation and logging. If a client handles the Everything server correctly, it handles most of the protocol.
It is not a business tool. It does not connect to any real system.
This is a reference server from the Model Context Protocol project. Reference servers show how the protocol works and are useful for learning and prototypes. Check the project notes before relying on one in production. One of its demo tools returns the server process environment, which could expose secrets if the server runs with sensitive environment variables. Run it only in a clean test setup.
We use servers like this when building custom MCP clients and servers for clients, to confirm that every feature behaves as expected. See MCP integration.
Use cases
Best business use cases
Client testing
Learning MCP
Debugging
SDK checks
Demos
Tools
Available tools
Tool names as published by the maintainer at review time. Versions change, so check the repository for the current list.
Read and write: Test only: demo tools; get-env exposes the server process environment.
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echoEcho back the message you send.
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get-sumAdd two numbers.
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get-tiny-imageReturn a small test image.
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get-structured-contentShow structured output with an output schema.
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get-resource-linksReturn a list of resource links.
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trigger-long-running-operationSimulate a long task with progress updates.
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trigger-sampling-requestAsk the client's model to generate a reply.
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trigger-elicitation-requestAsk the user for input through a form.
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toggle-simulated-loggingTurn simulated log messages on or off.
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get-envReturn the server's environment variables.
Workflows
Example workflows
Test a new MCP client
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1
Start the Everything server in a clean environment.
-
2
Connect your client.
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3
Call each tool.
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4
Check structured content and long-running operations.
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5
Fix client issues found.
Learn the protocol
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1
Connect it to Claude Desktop.
-
2
Ask the assistant to list tools.
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3
Try each one.
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4
Watch sampling and elicitation requests.
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5
Read the source alongside.
Prompts
Example prompts
“List every tool this server provides and what each one demonstrates.”
“Call the long-running operation tool and report its progress.”
“Return the structured content example.”
Setup
Installation and configuration
Examples for Claude Desktop and Claude Code. Replace the placeholder values with your own keys, and store secrets outside version control.
Claude Desktop: claude_desktop_config.json
{
"mcpServers": {
"everything": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-everything"
]
}
}
}Claude Code: terminal
claude mcp add everything -- npx -y @modelcontextprotocol/server-everything- Local server: stdio; @modelcontextprotocol/server-everything; mcp/everything; npx @modelcontextprotocol/server-everything streamableHttp.
Security
Security considerations
-
Environment exposure
A demo tool returns the environment. Run it without secrets.
-
Test only
Never connect it to business systems.
-
Clean setup
Use an isolated test environment.
-
Not for production
It is a demonstration server.
Related servers
Servers that pair well with it
Time
The MCP project's Time reference server gives AI the current time in any time zone and converts times between zones.
Fetch
The MCP project's reference Fetch server lets AI download a web page and read it as clean text or markdown.
Filesystem
The MCP project's Filesystem reference server lets AI read, write, edit, move and search files, only inside folders you allow.
Keep exploring
Solutions and services that use it
Related services
View all related services- MCP integration Connect AI assistants to your CRM, files, databases and tools through Model Context Protocol servers, with safe permissions.
- AI copilots AI helpers built into your product or internal tools that draft, summarize and suggest while people decide.
- Automation and Integrations CRM, payment and API integrations, MCP connections and workflows that stop people copying data by hand.
- MVP development A first version with just enough features to put in front of real users and learn what to build next.
- API integration Make two systems share data reliably, with retries, logging and alerts when something goes wrong.
- Legacy modernization Replace an aging system step by step, with the business running normally while the new parts take over.
Solutions
View all solutions- Internal help desk assistant An assistant in Slack or Teams that answers policy and how-to questions from your handbooks and opens tickets when needed.
- Approval workflows Requests, approvals and reminders in one place, with clear owners and deadlines instead of long email threads.
- AI sales research agent Short, sourced briefings on each prospect before a call, drafted by an AI agent from public information and your CRM.
Guides and articles
View all guides and articles- How to build an AI workflow with MCP servers Plan, connect and test an AI workflow that uses MCP servers, from a single task to a reliable process.
- Where AI helps in development, and where it does not An honest map of the development tasks AI speeds up and the ones that still need experienced people.
- What are AI agents and how do businesses use them? What AI agents are, real business uses, the controls they need and how to start with one safely.
- AI chatbot vs AI agent What separates a chatbot that answers from an agent that acts, and when you need each.
AI models
View all ai models- Mistral Medium 3.5 A newer open-weight Mistral model for agent and coding work, with image input, tool calling, structured outputs and a 256K window.
- Coding Models that write, review and explain code, and power coding assistants and developer tools.
- Claude Opus 5.5 Anthropic's recommended starting point for most serious work: long-running agentic coding and knowledge work, with a 1M token context window.
- Codestral 25.08 Mistral's low-latency coding model for code completion and generation, with fill-in-the-middle support, tool calling and a 128K window.
- GPT-6 Sol The middle model of the GPT-6 family, positioned for complex coding and agentic workflows at a mid price level.
- Qwen3-Coder Qwen's open-weight coding models under Apache 2.0, from the efficient Qwen3-Coder-Next to the large 480B model, with tool use and long context.
Glossary terms
View all glossary terms- API integration An API integration connects two or more systems through their APIs so data and actions flow between them automatically.
- AI agent An AI agent is software that uses a language model to plan steps, call tools and act toward a goal, instead of only answering one question.
- Claude Code Claude Code is Anthropic's agentic coding tool, which works in a developer's terminal, IDE, desktop app or browser to read code, run commands and make changes.
- AI copilot An AI copilot is an assistant built into a tool people already use, which suggests, drafts and explains while the person stays in control.
- Model Context Protocol The Model Context Protocol, or MCP, is an open standard for connecting AI assistants to external tools and data in a consistent way.
- Automation Automation is using software to perform a task or process with little or no human effort each time it runs.
FAQ
Questions people ask us
Have a question that is not here? Ask us directly.
No. It is for developers testing MCP clients.
In a clean test environment, yes. One tool returns environment variables, so avoid running it with secrets.
The Model Context Protocol project.