DMVCFramework MCP
БесплатноНе проверенMCP server implementation for Delphi applications using DMVCFramework, exposing tools, resources, and prompts via HTTP streamable and stdio transports.
Описание
MCP server implementation for Delphi applications using DMVCFramework, exposing tools, resources, and prompts via HTTP streamable and stdio transports.
README
MCP for Delphi
Server · Client · Agent — a full-stack MCP toolkit for DMVCFramework
A production-ready Model Context Protocol (MCP) toolkit for Delphi. It is not just a server library — it gives Delphi the complete MCP triangle in one package.
📖 Full documentation & guide → www.danieleteti.it/mcp-server-delphi
This README is just a hook. Every detail — getting started, API reference, the client, the agent, the REST→MCP bridge, configuration and testing — lives in the official documentation.
What is this?
Most "MCP for X" libraries only let you build a server the AI calls into. This one gives Delphi all three corners of the MCP world:
| Role | What it does | |
|---|---|---|
| 🟢 | Server | Expose your Delphi tools, resources, and prompts to AI assistants (Claude, Gemini, ChatGPT, …) over HTTP or stdio — attribute-driven, zero boilerplate. |
| 🔵 | Client | Consume any spec-compliant MCP server from your own Delphi code with TMCPClient (Streamable HTTP) or TMCPStdioClient (spawns a server as a child process and talks over pipes). |
| 🟣 | Agent | Drive an MCP server from an LLM with TMCPOpenAIAgent — a complete agent loop (tool discovery → LLM round-trips → tool dispatch → token accounting) that works with any OpenAI-compatible model: OpenAI, OpenRouter, Anthropic-compat, Together, Groq, Ollama, vLLM, llama.cpp --api. |
| 🌉 | REST → MCP Bridge | Auto-expose an existing DMVCFramework REST API as MCP tools by scanning the engine's routes via RTTI. Make your current backend AI-ready without writing a single tool by hand. |
In short: build AI-powered Delphi applications where Delphi is the server, the client, and the agent.
🚀 MCP with DMVCFramework? Sure — even for on-premises AI engines.
Expose your ERP and let a Delphi-side agent chain your tools. Ask: "Reorder customer C-1024's best-selling product from last March — but only if they're within their credit limit." The agent finds March's top product, reads the customer's balance, decides, and drafts the invoice — several tool calls, planned on the fly, all against your data. 💡
Features at a glance
- MCP Protocol 2025-03-26 compliant
- Server, client AND agent in one library — plus a REST→MCP bridge
- Attribute-driven tool/resource/prompt registration using RTTI — no manual wiring
- Dual transport, server and client side: Streamable HTTP and stdio
- Type-safe parameter binding with automatic JSON Schema generation
- Rich content types: Text, Image, Audio, Embedded Resources — with a fluent multi-content API
- URI resource templates (RFC 6570 Level 1)
- Session management with automatic cleanup
- DMVCFramework integration via the idiomatic
PublishObjectpattern - Apache 2.0 — free for commercial and personal use
A 30-second taste
Expose a tool (server):
[MCPTool('reverse_string', 'Reverses a string')]
function ReverseString(
[MCPParam('The string to reverse')] const Value: string
): TMCPToolResult;
Call a server (client):
LClient := TMCPClient.Create('http://localhost:8080/mcp');
LClient.Initialize;
WriteLn(LClient.CallTool('reverse_string',
TJSONObject.Create.AddPair('Value', 'hello')));
Drive a server from an LLM (agent):
LAgent := TMCPOpenAIAgent.Create('http://localhost:8080/mcp', LApiKey, 'gpt-4o-mini');
LAgent.SystemPrompt := 'You are a helpful Delphi-powered assistant.';
LResult := LAgent.Run(LUserMessages); // tool discovery + LLM loop + dispatch
WriteLn(LResult.Content);
👉 Full, runnable examples and the complete API are in the documentation.
Quick Start
Copy a ready-to-run Quick Start project and customize it — all share the same provider units in quickstart/shared/:
| Project | Role | Transport | Use when |
|---|---|---|---|
| quickstart/quickstart/ | Server | HTTP + stdio | You want a network server AI clients connect to via HTTP |
| quickstart/quickstart_stdio/ | Server | stdio only | You want the AI client (e.g. Claude Desktop) to launch the server locally |
| quickstart/quickstart_stdio_agent/ | Agent (host+client) | stdio | You want a Delphi-side AI agent that spawns and consumes a stdio MCP server, driven by an LLM |
Open the .dproj in Delphi, add DMVCFramework and this repo's sources/ to the search path, build, run. Step-by-step instructions, IDE wiring, and how to connect Claude Desktop / Gemini CLI / Claude Code / Continue are all in the documentation.
Testing ✅
Extensively tested by four independent compliance suites: a Python HTTP suite (185 cases), a Python stdio suite (147 cases), a TMCPClient suite (21 Delphi cases, run over both HTTP and stdio), and a TMCPOpenAIAgent suite (8 Delphi cases driving the agent loop against an embedded fake LLM). See the documentation for how to build and run them.
Requirements
- Delphi 11+ (Alexandria) or later
- DMVCFramework 3.5.x
License
Apache License 2.0 — see LICENSE.
Links
- 📖 Official Documentation & Full Guide ← start here
- Model Context Protocol Specification
- DMVCFramework
- Issue Tracker
Built with ❤️ by Daniele Teti
Установка DMVCFramework MCP
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/danieleteti/mcp-server-delphiFAQ
DMVCFramework MCP MCP бесплатный?
Да, DMVCFramework MCP MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для DMVCFramework MCP?
Нет, DMVCFramework MCP работает без API-ключей и переменных окружения.
DMVCFramework MCP — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить DMVCFramework MCP в Claude Desktop, Claude Code или Cursor?
Открой DMVCFramework MCP на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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