Everything
MCP ServerFree** - Reference / test server with prompts, resources, and tools
Capabilities10 decomposed
mcp protocol primitives demonstration via reference server
Medium confidenceImplements a complete reference server showcasing all four core MCP capability primitives (Tools, Resources, Prompts, Roots) through a unified TypeScript SDK interface. The server exposes these capabilities via JSON-RPC 2.0 protocol over stdio/SSE transports, allowing LLM clients to discover and invoke server-side functionality through standardized message schemas. This is an educational implementation designed to teach developers the exact patterns and SDK usage required to build their own MCP servers.
Serves as the official MCP reference implementation maintained by the MCP steering group, demonstrating all four protocol primitives (Tools, Resources, Prompts, Roots) in a single cohesive TypeScript codebase using the canonical MCP SDK patterns, rather than scattered examples across multiple repositories
More authoritative and complete than third-party MCP examples because it's the official reference maintained alongside the protocol specification itself, ensuring alignment with the latest MCP standards
tool capability exposure via schema-based function registry
Medium confidenceExposes callable tools to LLM clients through a schema-based function registry that defines tool names, descriptions, input schemas (JSON Schema format), and handler implementations. The server registers tools with the MCP SDK, which serializes them into the protocol's tool definition format and responds to tool_call requests with execution results. Tools are invoked through a standardized call pattern where the client sends tool name + parameters, the server executes the handler, and returns structured results or errors.
Uses the MCP SDK's native tool registration pattern with JSON Schema validation, which provides automatic schema serialization and client-side discovery without requiring manual OpenAI/Anthropic function-calling API adapters, making it transport-agnostic and protocol-native
Simpler than building tool-calling adapters for each LLM provider because MCP handles schema standardization and client discovery, allowing one tool definition to work across any MCP-compatible client
resource exposure with uri-based content serving
Medium confidenceExposes static or dynamic content as resources through a URI-based addressing scheme, where clients request resources by URI and the server returns content (text, code, structured data) along with MIME type metadata. Resources are registered with the MCP SDK with URI templates, descriptions, and content handlers that fetch or generate content on demand. The server maintains a resource list that clients can query to discover available resources, enabling LLMs to reference external knowledge or data sources.
Implements resources as first-class MCP primitives with URI-based addressing and automatic client discovery, rather than embedding content in prompts or requiring clients to make separate HTTP requests, enabling cleaner separation of concerns between LLM logic and data access
More efficient than prompt-based context injection because resources are fetched on-demand and can be updated server-side without redeploying the LLM, and more standardized than custom HTTP endpoints because MCP handles discovery and transport
prompt template exposure with variable substitution
Medium confidenceExposes reusable prompt templates through the MCP SDK that clients can discover and instantiate with variable substitution. Prompts are registered with names, descriptions, argument schemas, and template content that supports variable placeholders (e.g., {{variable}}). When a client requests a prompt, the server substitutes provided arguments into the template and returns the rendered prompt text. This enables LLM clients to use server-defined prompts for consistent, parameterized interactions.
Treats prompts as discoverable, versioned server-side resources rather than client-side strings, enabling centralized prompt management and allowing LLM clients to request domain-specific prompts by name without hardcoding template text
More maintainable than embedding prompts in client code because prompt updates happen server-side, and more discoverable than prompt libraries because clients can query available prompts and their argument schemas
roots declaration for workspace/project context scoping
Medium confidenceDeclares workspace or project roots that define the scope of resources and tools available to LLM clients, allowing servers to communicate which directories, repositories, or logical boundaries the client should operate within. Roots are registered with the MCP SDK and communicated to clients during capability discovery, enabling clients to understand the context boundaries for file operations, resource access, and tool execution. This is particularly useful for multi-project environments where different clients need different access scopes.
Implements roots as a first-class MCP primitive for declaring workspace context boundaries, rather than relying on implicit filesystem permissions or client-side configuration, enabling servers to explicitly communicate scope to clients during capability discovery
Clearer than implicit filesystem permissions because roots are explicitly declared and discoverable, and more flexible than hardcoded paths because roots can be configured per server instance
json-rpc 2.0 protocol transport abstraction
Medium confidenceAbstracts the underlying transport mechanism (stdio, SSE, WebSocket) behind a unified JSON-RPC 2.0 message protocol, allowing MCP servers to communicate with clients regardless of transport layer. The MCP SDK handles serialization/deserialization of JSON-RPC messages, request/response correlation, and error handling, while the server implementation remains transport-agnostic. This enables the same server code to work over stdio (for local CLI tools), SSE (for HTTP), or WebSocket (for real-time connections) without modification.
Provides transport abstraction through the MCP SDK's unified interface, allowing servers to be written once and deployed over stdio, SSE, or WebSocket without code changes, rather than requiring separate implementations per transport like traditional RPC frameworks
More flexible than REST APIs because transport is abstracted and clients can choose the best transport for their environment, and more standardized than custom RPC protocols because it uses JSON-RPC 2.0 with MCP-specific extensions
capability discovery and schema advertisement
Medium confidenceImplements the MCP protocol's capability discovery mechanism where servers advertise available tools, resources, prompts, and roots to clients through standardized schema messages. When a client connects, the server responds to discovery requests with complete capability definitions including names, descriptions, input/output schemas, and metadata. This enables clients to dynamically discover what the server can do without hardcoding capability lists, and to validate parameters before invoking tools or requesting resources.
Implements discovery as a core protocol feature with standardized schema advertisement, rather than requiring clients to hardcode capability lists or parse documentation, enabling true dynamic capability discovery and client-side validation
More discoverable than REST APIs with OpenAPI specs because discovery is built into the protocol and happens at connection time, and more flexible than static tool lists because capabilities can be updated server-side
educational reference patterns for mcp sdk usage
Medium confidenceProvides working code examples demonstrating best practices for using the MCP TypeScript SDK, including proper server initialization, capability registration, error handling, and transport configuration. The Everything server serves as a teaching tool showing how to structure MCP server code, organize handlers, define schemas, and respond to client requests. Developers can study the source code to understand SDK patterns before building their own servers, reducing the learning curve for MCP adoption.
Serves as the official MCP reference implementation maintained by the MCP steering group, providing authoritative examples of SDK usage patterns that are guaranteed to align with the current protocol specification and SDK API
More authoritative than third-party tutorials because it's maintained alongside the SDK itself, ensuring examples stay current with API changes and best practices
multi-capability integration testing framework
Medium confidenceProvides a complete, integrated example of all MCP capabilities (tools, resources, prompts, roots) working together in a single server, enabling developers to test how different capabilities interact and how clients handle mixed capability types. The server demonstrates patterns for coordinating between tools and resources (e.g., a tool that returns a resource URI), prompts that reference tools, and roots that scope resource access. This integration testing capability helps developers understand the full MCP ecosystem before building specialized servers.
Provides a single, integrated reference implementation that demonstrates all MCP capabilities working together, rather than separate examples for each capability type, enabling developers to understand how capabilities compose and interact
More comprehensive than single-capability examples because it shows real-world patterns where tools reference resources, prompts guide tool usage, and roots scope access, providing a more complete picture of MCP server design
typescript sdk reference for mcp server development
Medium confidenceDemonstrates the MCP TypeScript SDK API surface through working code, showing how to use SDK classes and methods for server initialization, capability registration, request handling, and response formatting. The server code illustrates SDK patterns for creating Server instances, registering tools/resources/prompts/roots, implementing handlers, and managing the request/response lifecycle. Developers can reference the source code to understand SDK capabilities and patterns before building their own servers.
Provides working code examples of the MCP TypeScript SDK API, allowing developers to learn by reading and running actual server code rather than relying solely on API documentation or tutorials
More practical than API documentation alone because developers can run the code and see SDK behavior in action, and more authoritative than third-party tutorials because it's maintained alongside the SDK
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
Related Artifactssharing capabilities
Artifacts that share capabilities with Everything, ranked by overlap. Discovered automatically through the match graph.
@modelcontextprotocol/server-everything
MCP server that exercises all the features of the MCP protocol
@msfeldstein/mcp-test-servers
A collection of MCP test servers including working servers (ping, resource, combined, env-echo) and test failure cases (broken-tool, crash-on-startup)
@transcend-io/mcp-server-core
Shared infrastructure for Transcend MCP Server packages
Spring AI MCP Server
** - Provides auto-configuration for setting up an MCP server in Spring Boot applications.
mcp-server
mcp server
example-remote-server
A hosted version of the Everything server - for demonstration and testing purposes, hosted at https://example-server.modelcontextprotocol.io/mcp
Best For
- ✓Developers building custom MCP servers for the first time
- ✓Teams evaluating MCP as a protocol for LLM-tool integration
- ✓Contributors to the MCP ecosystem learning reference patterns
- ✓Developers building LLM agents that need to perform actions (API calls, file operations, database queries)
- ✓Teams integrating LLMs with existing backend services via MCP
- ✓Builders creating AI assistants that require deterministic, auditable tool execution
- ✓Teams building RAG (Retrieval-Augmented Generation) systems where resources are fetched on-demand
- ✓Developers exposing documentation, code repositories, or knowledge bases to LLMs
Known Limitations
- ⚠Reference implementation only — lacks production-grade error handling, monitoring, and observability
- ⚠No built-in authentication or authorization beyond basic security patterns
- ⚠Simplified state management without persistence or distributed coordination
- ⚠Educational scope means some edge cases and failure modes are not fully handled
- ⚠Tool schemas must be JSON Schema compatible — complex type systems require careful schema design
- ⚠No built-in rate limiting or quota management per tool
Requirements
Input / Output
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** - Reference / test server with prompts, resources, and tools
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