MCP and related terminology used in this project.
MCP (Model Context Protocol) : A protocol for AI models to access external tools, resources, and prompts in a standardized way.
MCP Server : A service that exposes tools, resources, and prompts via the MCP protocol. Built with Dedalus MCP.
MCP Client : An application (typically an AI assistant) that connects to MCP servers to use their capabilities.
Transport : The communication layer between client and server. Common transports: stdio, HTTP.
Tool : A function the AI can invoke to perform actions. Has a name, description, and JSON schema for parameters.
Resource : Data the AI can read. Identified by URI. Can be static or dynamic.
Resource Template
: A parameterized resource URI pattern (e.g., file://{path}). Allows dynamic resource generation.
Prompt : A reusable message template with optional parameters. Helps structure AI interactions.
Capability : A feature the server declares support for (tools, resources, prompts, etc.).
Initialize : The handshake between client and server. Exchanges capabilities and protocol version.
Notification : A one-way message that doesn't expect a response.
Request/Response : A message pair where the sender expects a reply.
Progress : Optional reporting of long-running operation status.
Context
: Request-scoped state available to tool/resource handlers. Access via get_context().
Decorator
: The @tool, @resource, @prompt syntax for registering handlers.
Handler : A function that implements a tool, resource, or prompt.
Service : Internal component managing a category of handlers (ToolService, ResourceService, etc.).
Connection : An active link to an MCP server. Manages lifecycle and communication.
Session : The period between initialize and disconnect. Maintains state.
Sampling : Client capability to generate AI completions. Server can request this.
Roots : Filesystem paths the client exposes to servers.
OAuth 2.1 : The authorization protocol used for secure MCP connections.
Bearer Token : A token included in requests to prove authorization.
Scope
: Permissions granted to a token (e.g., tools:read, resources:write).
MCPServer : The main class for building MCP servers in Dedalus MCP.
MCPClient : The main class for connecting to MCP servers.
Pydantic : The validation library used for type-safe parameters and responses.
- MCP Specification — Official protocol spec
- MCP Python SDK — Low-level SDK
- Dedalus MCP Documentation — Framework guides