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A .NET-based Model Context Protocol server and Python client for interacting with the Slack Web API. It enables AI models to manage channels, send messages, ret

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Описание

A .NET-based Model Context Protocol server and Python client for interacting with the Slack Web API. It enables AI models to manage channels, send messages, retrieve chat history, and handle emoji reactions.

README

A complete Model Context Protocol (MCP) implementation with four architectural layers.

Layer Language File(s)
1 — Users Python 3.11+ client-python/main.py
2 — Prompt + Agent Python 3.11+ client-python/agent/agent.py
3 — MCP Client/Server Python + C# client-python/transport/mcp_client.py · server-csharp/
4 — Slack C# / .NET 8 server-csharp/Services/SlackService.cs

Architecture

  👤 User(s)
  (human operators / end-users)
       │  natural language input
       ▼
┌──────────────────────────────────────────────────────────┐
│  Prompt + Agent Layer                                    │
│                                                          │
│  Claude (Anthropic) ──or── External Agent                │
│    • interprets user intent                              │
│    • decides which MCP tool(s) to call                   │
│    • formats results back to the user                    │
└──────────────────────┬───────────────────────────────────┘
                       │  tool calls
                       ▼
┌──────────────────────────────────────────────────────────┐
│  Python MCP Client  (client-python/transport/)           │
│                                                          │
│  McpClient                                               │
│    └── StdioTransport                                    │
│          ├── spawns: dotnet run SlackMcpServer           │
│          └── JSON-RPC 2.0 over stdin / stdout            │
└──────────────────────┬───────────────────────────────────┘
                       │  stdio
┌──────────────────────▼───────────────────────────────────┐
│  C# MCP Server  (server-csharp/)                         │
│                                                          │
│  Program.cs  (stdio loop)                                │
│    └── ToolRegistry  (dispatch)                          │
│          └── SlackService  (Slack Web API)               │
└──────────────────────┬───────────────────────────────────┘
                       │  HTTPS
┌──────────────────────▼───────────────────────────────────┐
│  Slack                                                   │
│                                                          │
│  • send_message     → post to channel or thread          │
│  • get_history      → read recent messages               │
│  • list_channels    → browse workspace channels          │
│  • create_channel   → open a new public channel          │
│  • add_reaction     → emoji-react to a message           │
│  • list_users       → enumerate workspace members        │
└──────────────────────────────────────────────────────────┘

MCP Protocol Flow

Python Client                    C# Server
     │                               │
     │── initialize ────────────────►│
     │◄─ InitializeResult ───────────│
     │── initialized (notification) ►│
     │── tools/list ────────────────►│
     │◄─ ListToolsResult ────────────│
     │── tools/call {name, args} ───►│
     │◄─ CallToolResult ─────────────│

Layer Responsibilities

Layer 1 — 👤 Users (main.py)

Entry point for human operators. Provides an interactive REPL or single-prompt CLI. Has no knowledge of Slack or MCP — it only calls agent.handle(prompt).

Layer 2 — Prompt + Agent (agent/agent.py)

Interprets natural language intent and decides which MCP tool to call. The _resolve_intent() method is rule-based by default — replace it with a real LLM call (see comments in the file). Formats raw tool output into human-readable responses.

Layer 3 — MCP Transport (transport/mcp_client.py + server-csharp/)

Pure protocol layer. The Python side spawns the C# process and speaks JSON-RPC 2.0 over stdio. The C# side receives requests, dispatches to ToolRegistry, and writes responses. Neither side knows about user intent.

Layer 4 — Slack (server-csharp/Services/SlackService.cs)

Deepest layer. Each of the six methods maps directly to one Slack Web API endpoint. No MCP concepts here — just HTTP calls and typed DTOs.


Prerequisites

Tool Version
Python 3.11+
.NET SDK 8.0+
Slack Bot Token xoxb-…

Slack Bot Scopes Required

Go to api.slack.com/apps → OAuth & Permissions → Bot Token Scopes:

Scope Used by
chat:write send_message
channels:history get_history
channels:read list_channels
channels:write create_channel
reactions:write add_reaction
users:read list_users

Quick Start

# 1. Set your Slack bot token
export SLACK_BOT_TOKEN="xoxb-your-token-here"

# 2. Build the C# server
cd server-csharp
dotnet build

# 3. Run the interactive client
cd ../client-python
python main.py --server-cmd "dotnet run --project ../server-csharp/SlackMcpServer.csproj"

# Or run a single prompt
python main.py --prompt "List all channels"

Connecting a Real LLM (Claude)

Open client-python/agent/agent.py and replace _resolve_intent() with:

import anthropic

def _resolve_intent(self, prompt: str) -> Intent:
    client = anthropic.Anthropic()
    response = client.messages.create(
        model="claude-opus-4-6",
        max_tokens=1024,
        tools=self._client.tools,   # pass MCP schemas directly
        messages=[{"role": "user", "content": prompt}],
    )
    tool_use = next(b for b in response.content if b.type == "tool_use")
    return Intent(
        tool=tool_use.name,
        args=tool_use.input,
        explanation=prompt,
    )

Install the SDK: pip install anthropic


Running Tests

cd client-python
pip install pytest pytest-asyncio
python -m pytest tests/ -v

Tests are split by layer:

  • tests/test_agent.py — Layer 2: intent resolution and response formatting
  • tests/test_transport.py — Layer 3: JSON-RPC transport and MCP client

Project Structure

mcp-slack/
├── server-csharp/                   # Layer 3 (server) + Layer 4
│   ├── SlackMcpServer.csproj
│   ├── Program.cs                   # stdio JSON-RPC loop
│   ├── Models/
│   │   └── McpModels.cs             # JSON-RPC + MCP protocol types
│   ├── Services/
│   │   └── SlackService.cs          # Layer 4 — Slack Web API
│   └── Tools/
│       └── ToolRegistry.cs          # MCP tool definitions + dispatcher
│
└── client-python/                   # Layers 1, 2, 3 (client)
    ├── main.py                      # Layer 1 — User entry point
    ├── agent/
    │   ├── __init__.py
    │   └── agent.py                 # Layer 2 — Prompt + Agent
    ├── transport/
    │   ├── __init__.py
    │   └── mcp_client.py            # Layer 3 — MCP transport
    ├── tests/
    │   ├── conftest.py
    │   ├── test_agent.py
    │   └── test_transport.py
    ├── pytest.ini
    └── requirements.txt

Troubleshooting

Issue Fix
SLACK_BOT_TOKEN is not set export SLACK_BOT_TOKEN="xoxb-..."
channel_not_found Use a Channel ID like C012AB3CD, not #general
not_in_channel Invite the bot to the channel first
Server won't start Run dotnet build in server-csharp/ first
Intent not recognized Extend _resolve_intent() or plug in a real LLM

from github.com/antonhofstader/SLACK-MCP

Установка Slack

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/antonhofstader/SLACK-MCP

FAQ

Slack MCP бесплатный?

Да, Slack MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Slack?

Нет, Slack работает без API-ключей и переменных окружения.

Slack — hosted или self-hosted?

Доступен hosted-вариант: Unyly запускает сервер в облаке, локальная установка не обязательна.

Как установить Slack в Claude Desktop, Claude Code или Cursor?

Открой Slack 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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