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bobwares
by bobwares
MCP-based flow Actors.md1.39 kB
1. **User** The human who types requests (e.g. “Summarize last quarter’s sales figures”) and reads the agent’s responses. 2. **UI (User Interface)** The front-end component (web chat window, mobile app, etc.) that captures the user’s input, displays streaming tokens, shows status indicators, and renders final messages or tool outputs (charts, tables, images). 3. **Agent** Your MCP-enabled client library. It: * Receives user messages from the UI * Decides when to fetch external context or invoke tools * Assembles prompts (system + user + context) for the LLM * Streams tokens back to the UI * Parses the LLM’s tool calls and manages tool-result injection 4. **Context Provider(s)** External data sources or services (databases, search indexes, document stores) that reply to the agent’s `ContextFetch` requests with relevant information segments. 5. **LLM (Large Language Model) Endpoint** The language model API (e.g. OpenAI’s `chat/completions`) that, given the assembled prompt, generates streaming text and/or structured tool-invocation instructions. 6. **Tool Service(s)** Modular services (chart generators, calculators, data-transformers, etc.) registered via MCP. When the LLM issues a tool call, the agent forwards the call to the appropriate tool service and later merges its output back into the conversation.

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