linkedin-mcp-oauth

linkedin-mcp-oauth

Remote MCP server for LinkedIn hosted on Azure Functions, enabling profile retrieval and post publishing through OAuth.

Category
访问服务器

README

LinkedIn MCP Server (Azure Functions)

A remote Model Context Protocol server for LinkedIn, hosted on Azure Functions using the official Azure Functions MCP extension. It exposes personal LinkedIn tools to MCP clients such as GitHub Copilot (VS Code) and Claude Desktop.

Tools

Tool Description
get_my_profile Returns the authenticated owner's LinkedIn profile (GET /v2/userinfo, OpenID Connect).
create_post Publishes a public text post on the owner's LinkedIn feed (POST /v2/ugcPosts, scope w_member_social).
get_auth_status Reports token validity, expiration dates and available scopes.

Architecture

flowchart LR
    subgraph Client
        C[Copilot / MCP client]
    end
    subgraph "Azure Functions (Flex Consumption)"
        M[mcpTool triggers<br/>get_my_profile · create_post · get_auth_status]
        L[GET /auth/login]
        CB[GET /auth/callback]
        TS[(Table Storage<br/>tokens)]
    end
    C -- "streamable HTTP /runtime/webhooks/mcp" --> M
    L -- 302 --> LI[LinkedIn OAuth]
    LI -- code --> CB
    CB --> TS
    M --> TS
    M --> API[api.linkedin.com]

Why TypeScript? The MCP extension supports several stacks, but TypeScript (app.mcpTool, @azure/functions ≥ 4.9.0 + extension bundle [4.0.0, 5.0.0)) is first-class, requires no worker-specific package, and matches the Node.js ecosystem this project is inspired by. C# isolated (Microsoft.Azure.Functions.Worker.Extensions.Mcp) would be the alternative for .NET teams.

OAuth: LinkedIn's member APIs (userinfo, ugcPosts) do not support client_credentials. A one-time 3-legged authorization-code flow is required: open /auth/login, consent in the browser, and the server stores the access token (60 days) + refresh token (1 year) in Azure Table Storage. The access token is refreshed automatically whenever it has less than 7 days left.

1. Create the LinkedIn app

  1. Go to the LinkedIn Developer PortalCreate app.
  2. In the app Products tab, request/enable:
    • Sign In with LinkedIn using OpenID Connect (scopes openid, profile)
    • Share on LinkedIn (scope w_member_social)
  3. In the Auth tab, add the redirect URL:
    • Local: http://localhost:7071/auth/callback
    • Azure (after deploy): https://<your-function-app>.azurewebsites.net/auth/callback
  4. Note the Client ID and Client Secret.

2. Run locally

Prerequisites: Node.js 20+, Azure Functions Core Tools v4.0.7030+, and Azurite (for Table Storage).

npm install
cp local.settings.json.template local.settings.json   # fill in LINKEDIN_CLIENT_ID / LINKEDIN_CLIENT_SECRET
azurite --silent &                                     # or use a real storage account connection string
npm run build
func start

Then open http://localhost:7071/auth/login in a browser and complete the LinkedIn consent once.

Connect a client locally

.vscode/mcp.json (or your client's equivalent):

{
  "servers": {
    "linkedin-local": {
      "type": "http",
      "url": "http://localhost:7071/runtime/webhooks/mcp"
    }
  }
}

3. Deploy to Azure

Prerequisites: Azure Developer CLI (azd).

azd init            # or run inside this folder directly
azd env set LINKEDIN_CLIENT_ID <your-client-id>       # optional — see below
azd env set LINKEDIN_CLIENT_SECRET <your-client-secret> # optional — see below
azd up

The Bicep parameters linkedInClientId / linkedInClientSecret are optional (default ''). If you skip the azd env set commands, deploy first and then set LINKEDIN_CLIENT_ID and LINKEDIN_CLIENT_SECRET manually in the Azure Portal (Function App → Settings → Environment variables). The /auth/login and /auth/callback endpoints return an explicit 500 error listing any missing app settings until they are configured.

This provisions (Bicep, infra/): a resource group, a Storage account (tokens table + host storage), Log Analytics + Application Insights, and a Flex Consumption (FC1) Function App running Node.js 22 — no VNet, no private endpoints, no Entra app.

After deployment:

  1. Add https://<your-function-app>.azurewebsites.net/auth/callback as a redirect URL in the LinkedIn app (Auth tab).

  2. Open https://<your-function-app>.azurewebsites.net/auth/login and complete the OAuth flow.

  3. Retrieve the MCP system key:

    az functionapp keys list --resource-group rg-<env-name> --name <function-app-name> --query systemKeys.mcp_extension --output tsv
    
  4. Configure your MCP client:

    {
      "inputs": [
        { "type": "promptString", "id": "mcp-key", "description": "MCP extension system key", "password": true }
      ],
      "servers": {
        "linkedin": {
          "type": "http",
          "url": "https://<your-function-app>.azurewebsites.net/runtime/webhooks/mcp",
          "headers": { "x-functions-key": "${input:mcp-key}" }
        }
      }
    }
    

Configuration

App setting Description
LINKEDIN_CLIENT_ID LinkedIn app client ID.
LINKEDIN_CLIENT_SECRET LinkedIn app client secret. For production, prefer a Key Vault reference (@Microsoft.KeyVault(...)) instead of a plain value.
BASE_URL Public base URL of the app, used to build the OAuth redirect URI. Set automatically by Bicep in Azure.
AzureWebJobsStorage Storage connection string — also used for the tokens table.

Project structure

├── host.json                  # MCP extension config (serverName, instructions) + extension bundle
├── package.json / tsconfig.json
├── azure.yaml                 # azd service definition
├── local.settings.json.template
├── src/
│   ├── index.ts
│   ├── functions/
│   │   ├── mcpTools.ts        # app.mcpTool: get_my_profile, create_post, get_auth_status
│   │   └── auth.ts            # GET /auth/login, GET /auth/callback (OAuth 3-legged)
│   └── lib/
│       ├── tokenStore.ts      # Azure Table Storage tokens + automatic refresh (< 7 days)
│       └── linkedinClient.ts  # /v2/userinfo, /v2/ugcPosts
└── infra/
    ├── main.bicep             # Flex Consumption + Storage + App Insights
    └── main.parameters.json

Credits & license

Inspired by Dishant27/linkedin-mcp-server (LinkedIn API usage patterns). This implementation is written from scratch around the Azure Functions MCP extension and 3-legged OAuth. Licensed under MIT.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选