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add-mcp-server

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업데이트2026년 5월 26일 11:54

Add a Model Context Protocol (MCP) server to a genai-tk project — config, credential management, and validation.

설치

Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.

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tclatos

tclatos/genai-tk

GitHub 저장소 열기 Creator 저장소 보기

다운로드

Manus에서 실행

Add an MCP Server

MCP (Model Context Protocol) servers expose tools to agents over a standardized JSON-RPC interface. genai-tk manages them through config/mcp_servers.yaml.

Step 1: Find or Implement the MCP Server

Use an existing server:

@modelcontextprotocol/server-filesystem — file system access
@modelcontextprotocol/server-brave-search — web search
@modelcontextprotocol/server-github — GitHub API
Browse: https://github.com/modelcontextprotocol/servers

Implement your own:
See examples/mcp_server/ for a Python MCP server skeleton.

Step 2: Add to mcp_servers.yaml

Edit config/mcp_servers.yaml:

mcp_servers:
  my_server:                        # ← key used in agent profiles
    transport: stdio                # stdio | sse
    command: npx
    args:
      - "-y"
      - "@modelcontextprotocol/server-brave-search"
    env:
      BRAVE_API_KEY: ${oc.env:BRAVE_API_KEY}  # env var interpolation
    enabled: true

  my_python_server:
    transport: stdio
    command: uv
    args:
      - run
      - python
      - examples/mcp_server/server.py
    enabled: true

Step 3: Reference in Agent Profile

In config/agents/langchain.yaml:

langchain_agents:
  my_agent:
    mcp_servers:
      - my_server
      - my_python_server

Step 4: Add Credentials

Add to .env (never commit this file):

BRAVE_API_KEY=bsk-xxxxx

Add to .env.example (commit this):

BRAVE_API_KEY=              # get from https://api.search.brave.com/

Step 5: Validate

cli mcp list                    # list configured servers
cli mcp test my_server          # verify connection
cli agents langchain -p my_agent "search for: Python MCP"

Transport Types

Transport	Use when	Notes
`stdio`	local process or Docker	default, most reliable
`sse`	remote/HTTP server	requires running server URL

For sse transport:

my_server:
  transport: sse
  url: http://localhost:8080/sse

Code Map

Concern	Path
MCP config	`config/mcp_servers.yaml`
MCP CLI commands	`genai_tk/cli/commands_mcp.py`
MCP docs	`docs/mcp-servers.md`
Example server	`examples/mcp_server/server.py`
Agent profiles	`config/agents/langchain.yaml`

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name	add-mcp-server
description	Add a Model Context Protocol (MCP) server to a genai-tk project — config, credential management, and validation.
tags	["mcp","tools","configuration"]
version	1.0

Add an MCP Server

MCP (Model Context Protocol) servers expose tools to agents over a standardized JSON-RPC interface. genai-tk manages them through config/mcp_servers.yaml.

Step 1: Find or Implement the MCP Server

Use an existing server:

@modelcontextprotocol/server-filesystem — file system access
@modelcontextprotocol/server-brave-search — web search
@modelcontextprotocol/server-github — GitHub API
Browse: https://github.com/modelcontextprotocol/servers

Implement your own:
See examples/mcp_server/ for a Python MCP server skeleton.

Step 2: Add to mcp_servers.yaml

Edit config/mcp_servers.yaml:

mcp_servers:
  my_server:                        # ← key used in agent profiles
    transport: stdio                # stdio | sse
    command: npx
    args:
      - "-y"
      - "@modelcontextprotocol/server-brave-search"
    env:
      BRAVE_API_KEY: ${oc.env:BRAVE_API_KEY}  # env var interpolation
    enabled: true

  my_python_server:
    transport: stdio
    command: uv
    args:
      - run
      - python
      - examples/mcp_server/server.py
    enabled: true

Step 3: Reference in Agent Profile

In config/agents/langchain.yaml:

langchain_agents:
  my_agent:
    mcp_servers:
      - my_server
      - my_python_server

Step 4: Add Credentials

Add to .env (never commit this file):

BRAVE_API_KEY=bsk-xxxxx

Add to .env.example (commit this):

BRAVE_API_KEY=              # get from https://api.search.brave.com/

Step 5: Validate

cli mcp list                    # list configured servers
cli mcp test my_server          # verify connection
cli agents langchain -p my_agent "search for: Python MCP"

Transport Types

Transport	Use when	Notes
`stdio`	local process or Docker	default, most reliable
`sse`	remote/HTTP server	requires running server URL

For sse transport:

my_server:
  transport: sse
  url: http://localhost:8080/sse

Code Map

Concern	Path
MCP config	`config/mcp_servers.yaml`
MCP CLI commands	`genai_tk/cli/commands_mcp.py`
MCP docs	`docs/mcp-servers.md`
Example server	`examples/mcp_server/server.py`
Agent profiles	`config/agents/langchain.yaml`