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LinkedIn MCP

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stickerdaniel

Open-source MCP server for LinkedIn. Give Claude and any MCP-compatible AI agent access to profiles, companies, jobs, and messages.

Publisherstickerdaniel
Repositorylinkedin-mcp-server
LanguagePython
Forks
622
Stars
3.6K
Available tools
0
Transport typestdio
Categories
LicenseApache-2.0
Links
  • Connect tools to AI workflows

    LinkedIn MCP exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    3.6K stars and 622 forks from the linked repository.

MCP Server for LinkedIn

An MCP server that connects AI assistants like Claude to LinkedIn through your own logged-in browser session. Look up profiles and companies, send messages, manage your inbox, or search for jobs. All browser actions run locally on your machine.

This is an independent open-source project, not affiliated with, authorized by, endorsed by, or sponsored by LinkedIn or Microsoft. LinkedIn is a trademark of LinkedIn Corporation and is used here only to identify the service this software interacts with.

This MCP server is supported by Unipile. Unipile is the fully managed cloud option for developers: a hosted LinkedIn API for Classic, Sales Navigator, and Recruiter that handles auth, sessions, and infrastructure for you.

Try Unipile free for 7 days →


Installation Methods - LinkedIn MCP Server

uvx Install MCP Bundle Codex Plugin Docker

ToolDescription
get_person_profileGet profile info with explicit section selection (experience, education, interests, honors, languages, certifications, skills, projects, contact_info, posts)
get_my_profileGet the authenticated user's own LinkedIn profile (same sections as get_person_profile)
connect_with_personSend a connection request or accept an incoming one, with optional note
get_sidebar_profilesExtract profile URLs from sidebar recommendation sections ("More profiles for you", "Explore premium profiles", "People you may know") on a profile page
get_inboxList recent conversations from the LinkedIn messaging inbox
get_conversationRead a specific messaging conversation by username or thread ID
search_conversationsSearch messages by keyword
send_messageCompose/send a new message to a LinkedIn user (requires confirmation; profile-based targeting may open a separate DM instead of replying in an existing thread — see #483)
get_company_profileExtract company information with explicit section selection (posts, jobs); about-section references may include a company_urn entry carrying the numeric id used by LinkedIn's people-search currentCompany URL facet
get_company_postsGet recent posts from a company's LinkedIn feed
search_companiesSearch for companies on LinkedIn by keywords
get_company_employeesList employees at a company from the /people/ page, with optional keyword filter
search_jobsSearch for jobs with keywords and location filters
get_saved_jobsList job postings saved by the authenticated user
search_peopleSearch for people by keywords, location, connection degree (1st/2nd/3rd), and current company
get_job_detailsGet detailed information about a specific job posting
get_feedGet recent posts from the authenticated user's home feed
search_postsSearch posts/content globally by keyword (the "Posts" tab) with an optional recency filter (past-24h/past-week/past-month); returns unordered candidate permalinks in references
close_sessionClose browser session and clean up resources

🚀 uvx Setup (Recommended)

Prerequisites: Install uv.

Installation

Client Configuration

json
{
  "mcpServers": {
    "mcp-server-linkedin": {
      "command": "uvx",
      "args": ["mcp-server-linkedin@latest"],
      "env": { "UV_HTTP_TIMEOUT": "300" }
    }
  }
}

The @latest tag turns on automatic updates, which keep the server working with LinkedIn's current page structure. The server starts quickly, prepares the shared Patchright Chromium browser cache in the background under ~/.linkedin-mcp/patchright-browsers, and opens a LinkedIn login browser window on the first tool call that needs authentication.

AI agent? Get a quick confirmation from the user before enabling automatic updates.

[!NOTE] Early tool calls may return a setup/authentication-in-progress error until browser setup or login finishes. If you prefer to create a session explicitly, run uvx mcp-server-linkedin@latest --login.

uvx Setup Help

  • Default (stdio): Standard communication for local MCP servers
  • Streamable HTTP: For a web-based MCP server
  • If no transport is specified, the server defaults to stdio
  • An interactive terminal without explicit transport shows a chooser prompt

Session:

  • --login - Open a browser to sign in and save the session
  • --import-from-browser [BROWSER] - Reuse a session from a locally signed-in Chromium browser (chrome, chromium, brave, edge, arc, vivaldi, helium, yandex, whale, auto). Bare flag picks auto, the most recently used browser with a live LinkedIn session.
  • --auto-import / --no-auto-import - Import a session from a signed-in local browser on the first tool call that needs one, before falling back to manual login (default: on). Skipped in Docker, behind a proxy, and on a non-loopback HTTP bind. On macOS the keychain may prompt once.
  • --logout - Clear the stored session
  • --login-viewer - Docker only: show the --login browser at a token-protected URL on port 6080 (see Authentication)
  • --user-data-dir PATH - Browser profile directory (default: ~/.linkedin-mcp/profile). Rotating or clearing a session deletes this directory and its parent, which holds the stored cookies and derived profiles.
  • --claim-profile-root - Take over a profile directory the server will not claim on its own, such as one whose parent already holds other files. Needed once per directory.

Transport:

  • --transport {stdio,streamable-http} - Force the transport mode (default: stdio)
  • --host HOST / --port PORT / --path PATH - HTTP server address (defaults: 127.0.0.1, 8000, /mcp)

Timeouts:

  • --timeout MS - Timeout for a single page operation (default: 5000)
  • --tool-timeout SECONDS - Timeout for a whole tool call (default: 180). Raise it for heavy scrapes, slow networks, or a cold-start browser.
  • --login-timeout SECONDS - How long the login browser waits for you to finish signing in (default: 1800; 0 = no limit). --login-viewer ends the session after 30 minutes either way.
  • --login-inline-wait SECONDS - How long a tool call waits for a login to finish before telling the model to retry (default: 25, max 45; 0 = return at once)

Shared browser:

  • --browser-wait SECONDS - How long to wait for another server process to hand over the shared browser (default: 25, max 45; 0 = report busy at once). Only matters with several MCP clients running at once.
  • --browser-min-hold SECONDS - Shortest time this process keeps the shared browser before handing it over (default: 20). Clamped to 3 seconds below --browser-wait, so raise that one along with it. Higher means fewer browser restarts but longer waits for other clients.
  • --browser-idle-timeout SECONDS - Close an idle browser and release the profile after this long without a tool call (default: 600; 0 = keep it open)

Browser:

  • --no-headless - Show the browser window (useful for debugging)
  • --chrome-path PATH - Path to a Chrome/Chromium executable
  • --proxy-server URL - Route browser traffic through a proxy, as scheme://host:port. Set it up before --login; see Using a proxy.

Other:

  • --log-level {DEBUG,INFO,WARNING,ERROR} - Logging level (default: WARNING)

If you are already signed into LinkedIn in Chrome, Chromium, Brave, Edge, Arc, Vivaldi, Helium, Yandex, or Naver Whale, you can skip the manual --login step and reuse that session:

bash
# Auto-pick the most recently used browser with a live LinkedIn session
uvx mcp-server-linkedin@latest --import-from-browser
# Or target a specific browser
uvx mcp-server-linkedin@latest --import-from-browser brave

This reads the browser's LinkedIn cookies, validates them against your feed, and saves them to ~/.linkedin-mcp/profile/, the same place --login writes to. Notes:

  • With several signed-in browsers, the most recently used live LinkedIn session is tried first. If LinkedIn rejects it (revoked or remote-logged-out), the next most recent is tried automatically; the first the server accepts is imported. There is no prompt to pick. Pass a browser name to target one specifically.
  • On macOS the OS keychain may prompt to allow access to the browser's Safe Storage. Close the source browser first for the most reliable read.
  • Cookies protected by Chrome 127+ app-bound encryption (v20) cannot be decrypted without OS elevation; in that case use --login instead.
  • Imported cookies match a real login's on-disk set. The local server reads them back in full from the saved profile; the Docker bridge narrows to the same minimal auth subset it uses for a normal session.

Basic Usage Examples:

bash
# Run with debug logging
uvx mcp-server-linkedin@latest --log-level DEBUG

HTTP Mode Example (for web-based MCP clients):

bash
uvx mcp-server-linkedin@latest --transport streamable-http --host 127.0.0.1 --port 8080 --path /mcp

Runtime server logs are emitted by FastMCP/Uvicorn.

Tool calls are serialized to protect the shared LinkedIn browser session, both within one server process and across separate ones. If you run several MCP clients at once, each starts its own server process, and only one of them uses the browser at a time; the others wait briefly and take over as soon as it finishes a call. A client that waits too long gets a "browser is busy" message and can simply retry. Use --log-level DEBUG to see the wait/acquire/release logs.

This covers processes on the same machine and in the same runtime. It does not extend between the host and a Docker container sharing the same ~/.linkedin-mcp directory, so do not run --login or --logout on the host while a container is running.

Test with mcp inspector:

  1. Install and run mcp inspector bunx @modelcontextprotocol/inspector
  2. Click pre-filled token url to open the inspector in your browser
  3. Select Streamable HTTP as Transport Type
  4. Set URL to http://localhost:8080/mcp
  5. Connect
  6. Test tools
  • Ensure you have uv installed: curl -LsSf https://astral.sh/uv/install.sh | sh
  • Check uv version: uv --version (should be 0.4.0 or higher)
  • On first run, uvx downloads all Python dependencies. On slow connections, uv's default 30s HTTP timeout may be too short. The recommended config above already sets UV_HTTP_TIMEOUT=300 (seconds) to avoid this.
  • Windows, DLL load failed while importing _greenlet: move to greenlet 3.5.5 or newer, whose published Windows wheels carry the C++ runtime inside the extension again. A fresh uvx run resolves that on its own; an environment that pins its dependencies needs uv lock --upgrade-package greenlet. Only greenlet 3.3.1 through 3.5.4 need MSVCP140.dll, which neither the python.org installer nor the uv-managed builds carry, and a greenlet built from source can need it at any version. Where the version cannot be moved, the Microsoft Visual C++ Redistributable supplies that DLL. Reported as greenlet#525, fixed in greenlet#526.
  • Browser profile is stored at ~/.linkedin-mcp/profile/
  • Managed browser downloads are cached at ~/.linkedin-mcp/patchright-browsers/
  • The browser cache keeps growing: a server upgrade can bring a new Chromium revision, and Patchright keeps the old one for as long as any installed version still references it. uvx keeps one archive per version you have ever run, so every one of them holds such a reference and the old revisions stay. The server logs a warning naming the revisions it is holding and how much space they take. To reclaim it, stop every LinkedIn MCP Server instance, delete ~/.linkedin-mcp/patchright-browsers/, and let the next launch download the current browser.
  • Make sure you have only one active LinkedIn session at a time
  • LinkedIn may require a login confirmation in the LinkedIn mobile app for --login
  • LinkedIn may show a captcha challenge during login. Run uvx mcp-server-linkedin@latest --login which opens a browser where you can solve it manually.
  • Page operations failing (elements not found, navigation hangs): increase the browser page-op timeout: --timeout 10000 or TIMEOUT=10000 (milliseconds, default 5000).
  • Entire tool calls timing out (e.g. multi-section profiles, cold-start Chromium, slow containers): increase the per-tool execution timeout: --tool-timeout 300 or TOOL_TIMEOUT=300 (seconds, default 180).
  • First tool call with no session: if a locally logged-in browser has a live LinkedIn session, the server auto-imports it (see AUTO_IMPORT_FROM_BROWSER / --auto-import) instead of forcing a manual login. On macOS the keychain may prompt once for Safe Storage access. If no importable browser session exists, it falls back to opening a login window and waits up to LOGIN_INLINE_WAIT seconds (default 25, max 45; --login-inline-wait) so a quick sign-in resolves in one call. If the wait elapses, the tool returns a pending signal and the model retries in about 30 seconds. Neither the auto-import nor the inline wait applies under Docker or when the server is bound to a non-loopback HTTP host. Create the session on the host with --login, or use the explicit Docker --login --login-viewer command.
  • Users on slow connections may need higher values for either.
  • If tool calls answer "No valid LinkedIn session is available in Docker" on a machine that is not a container, the runtime was misdetected. This happened on Linux hosts running a Docker daemon for unrelated services. Set LINKEDIN_MCP_CONTAINER=false to override the detection; true forces the opposite.
  • If Chrome is installed in a non-standard location, use --chrome-path /path/to/chrome
  • Can also set via environment variable: CHROME_PATH=/path/to/chrome
  • On macOS and Linux the browser must be at least as new as the one that last opened your profile, and the server refuses the launch otherwise. (Not on Windows: a browser there cannot be asked its version without starting one, so the check is off.) An older browser can silently drop stores a newer one wrote, the saved session among them, and the failure then looks exactly like an expired login. The message names both versions. Going back to the bundled Chromium after running a newer Chrome once is the usual way to meet this; either run the newer browser again, whichever one that was, or run --login, which moves the stored session aside and signs in fresh with the browser you have. --logout also clears it but discards the old session instead of keeping it recoverable, and it asks for confirmation on the terminal, so it is not usable from a server an MCP client started.
  • Only Chrome, Chromium and Chrome for Testing are compared this way. Forks number themselves differently (Vivaldi is on 7.x, Edge's build number sits far below Chrome's under the same major), so pointing CHROME_PATH at one turns the check off rather than producing a refusal nothing could satisfy.

📦 Claude Desktop MCP Bundle (formerly DXT)

Prerequisites: Claude Desktop.

One-click installation for Claude Desktop users:

  1. Download the latest .mcpb artifact from releases
  2. Click the downloaded .mcpb file to install it into Claude Desktop
  3. Call any LinkedIn tool

On startup, the MCP Bundle starts preparing the shared Patchright Chromium browser cache in the background. If you call a tool too early, Claude will surface a setup-in-progress error. On the first tool call that needs authentication, the server opens a LinkedIn login browser window and asks you to retry after sign-in.

MCP Bundle Setup Help

  • Claude Desktop starts the bundle immediately; browser setup continues in the background
  • If the Patchright Chromium browser is still downloading, retry the tool after a short wait
  • Managed browser downloads are shared under ~/.linkedin-mcp/patchright-browsers/
  • The browser cache keeps growing: Patchright keeps an old Chromium revision for as long as any installed version still references it, so an upgrade can leave both on disk. The server logs a warning naming what it holds. To reclaim the space, stop every LinkedIn MCP Server instance, delete ~/.linkedin-mcp/patchright-browsers/, and let the next launch download the current browser.
  • Windows, the bundle exits with DLL load failed while importing _greenlet: install the Microsoft Visual C++ Redistributable, or reinstall a bundle pinning greenlet 3.5.5 or newer, whose published Windows wheels carry the C++ runtime inside the extension again. A bundle pinning greenlet 3.3.1 through 3.5.4 needs MSVCP140.dll from that redistributable, which neither the python.org installer nor the uv-managed builds carry, and a greenlet built from source can need it at any version. The server names this itself on startup, and only after checking that the loader cannot produce that DLL. Reported as greenlet#525, fixed in greenlet#526.
  • Make sure you have only one active LinkedIn session at a time
  • LinkedIn may require a login confirmation in the LinkedIn mobile app for --login
  • LinkedIn may show a captcha challenge during login. Run uvx mcp-server-linkedin@latest --login which opens a browser where you can solve captchas manually. See the uvx setup for prerequisites.
  • Page operations failing (elements not found, navigation hangs): increase the browser page-op timeout: --timeout 10000 or TIMEOUT=10000 (milliseconds, default 5000).
  • Entire tool calls timing out (e.g. multi-section profiles, cold-start Chromium, slow containers): increase the per-tool execution timeout: --tool-timeout 300 or TOOL_TIMEOUT=300 (seconds, default 180).
  • First tool call with no session: if a locally logged-in browser has a live LinkedIn session, the server auto-imports it (see AUTO_IMPORT_FROM_BROWSER / --auto-import) instead of forcing a manual login. On macOS the keychain may prompt once for Safe Storage access. If no importable browser session exists, it falls back to opening a login window and waits up to LOGIN_INLINE_WAIT seconds (default 25, max 45; --login-inline-wait) so a quick sign-in resolves in one call. If the wait elapses, the tool returns a pending signal and the model retries in about 30 seconds. Neither the auto-import nor the inline wait applies under Docker or when the server is bound to a non-loopback HTTP host. Create the session on the host with --login, or use the explicit Docker --login --login-viewer command.
  • Users on slow connections may need higher values for either.
  • If tool calls answer "No valid LinkedIn session is available in Docker" on a machine that is not a container, the runtime was misdetected. This happened on Linux hosts running a Docker daemon for unrelated services. Set LINKEDIN_MCP_CONTAINER=false to override the detection; true forces the opposite.

🧩 Codex plugin

This repository includes an opt-in Codex plugin that bundles the MCP server. Add the repository marketplace and install the plugin:

bash
codex plugin marketplace add stickerdaniel/linkedin-mcp-server
codex plugin add linkedin-mcp-server@linkedin-mcp-server

🐳 Docker Setup

Authentication

Log in once. The container opens a LinkedIn login browser that you drive from your own browser tab.

macOS / Linux:

bash
# Create the directory first so the container can save your session into it
mkdir -p ~/.linkedin-mcp
docker run -it --rm \
  -v ~/.linkedin-mcp:/home/pwuser/.linkedin-mcp \
  -p 127.0.0.1:6080:6080 \
  stickerdaniel/linkedin-mcp-server:latest \
  --login --login-viewer

PowerShell (Windows):

powershell
$sessionDir = Join-Path $env:USERPROFILE ".linkedin-mcp"
New-Item -ItemType Directory -Force -Path $sessionDir | Out-Null
docker run -it --rm `
  -v "${sessionDir}:/home/pwuser/.linkedin-mcp" `
  -p 127.0.0.1:6080:6080 `
  stickerdaniel/linkedin-mcp-server:latest `
  --login --login-viewer

Open the full URL the command prints (it carries the access token) and sign in. The viewer closes itself afterwards; let the command exit on its own so the session is stored completely. It gives up after 30 minutes.

Keep the same host directory mounted at /home/pwuser/.linkedin-mcp on every later docker run, otherwise the server cannot find the session.

Configure Claude Desktop with Docker

macOS / Linux (absolute path in JSON):

json
{
  "mcpServers": {
    "mcp-server-linkedin": {
      "command": "docker",
      "args": [
        "run", "--rm", "-i",
        "-v", "/absolute/path/to/.linkedin-mcp:/home/pwuser/.linkedin-mcp",
        "stickerdaniel/linkedin-mcp-server:latest"
      ]
    }
  }
}

Spell that first path out in full. A client runs docker directly rather than through a shell, so a leading ~ reaches Docker unexpanded and it refuses the mount.

PowerShell (Windows): use a forward-slash JSON path. A backslash path like C:\Users\Alice\.linkedin-mcp fails JSON parsing because \U is an invalid escape. Use C:/Users/Alice/.linkedin-mcp instead, replacing Alice with your username.

json
{
  "mcpServers": {
    "mcp-server-linkedin": {
      "command": "docker",
      "args": [
        "run", "--rm", "-i",
        "-v", "C:/Users/Alice/.linkedin-mcp:/home/pwuser/.linkedin-mcp",
        "stickerdaniel/linkedin-mcp-server:latest"
      ]
    }
  }
}

[!NOTE] In PowerShell, ~ is not expanded inside a composite Docker -v argument. Use C:/Users/<you>/.linkedin-mcp or build the path with $env:USERPROFILE\.linkedin-mcp before passing it to Docker.

[!NOTE] Sessions expire over time. When tool calls start asking for authentication, repeat the login command above, or run uvx mcp-server-linkedin@latest --login on the host.

Docker Setup Help

  • Default (stdio): Standard communication for local MCP servers
  • Streamable HTTP: For a web-based MCP server
  • If no transport is specified, the server defaults to stdio
  • An interactive terminal without explicit transport shows a chooser prompt

Session:

  • --auto-import / --no-auto-import - Import a session from a signed-in local browser on the first tool call that needs one, before falling back to manual login (ignored in Docker). On macOS the keychain may prompt once.
  • --logout - Clear the stored session and every profile derived from it
  • --login-viewer - With --login, show the login browser at a token-protected URL on port 6080. Needs the profile mount from Authentication.
  • --user-data-dir PATH - Browser profile directory (default: ~/.linkedin-mcp/profile). Rotating or clearing a session deletes this directory and its parent, which holds the stored cookies and derived profiles.
  • --claim-profile-root - Take over a profile directory the server will not claim on its own, such as one whose parent already holds other files. Needed once per directory.

Transport:

  • --transport {stdio,streamable-http} - Force the transport mode (default: stdio)
  • --host HOST / --port PORT / --path PATH - HTTP server address (defaults: 127.0.0.1, 8000, /mcp)

Timeouts:

  • --timeout MS - Timeout for a single page operation (default: 5000)
  • --tool-timeout SECONDS - Timeout for a whole tool call (default: 180). Raise it for heavy scrapes, slow networks, or a cold-start browser.
  • --login-timeout SECONDS - How long the login browser waits for you to finish signing in (default: 1800; 0 = no limit). --login-viewer ends the session after 30 minutes either way.
  • --login-inline-wait SECONDS - How long a tool call waits for a login to finish before telling the model to retry (default: 25, max 45; 0 = return at once)

Shared browser:

  • --browser-wait SECONDS - How long to wait for another server process to hand over the shared browser (default: 25, max 45; 0 = report busy at once). Only matters with several MCP clients running at once.
  • --browser-min-hold SECONDS - Shortest time this process keeps the shared browser before handing it over (default: 20). Clamped to 3 seconds below --browser-wait, so raise that one along with it. Higher means fewer browser restarts but longer waits for other clients.
  • --browser-idle-timeout SECONDS - Close an idle browser and release the profile after this long without a tool call (default: 600; 0 = keep it open)

Browser:

  • --chrome-path PATH - Path to a Chrome/Chromium executable (rarely needed in Docker)
  • --proxy-server URL - Route browser traffic through a proxy, as scheme://host:port. Set it up before --login; see Using a proxy.

Other:

  • --log-level {DEBUG,INFO,WARNING,ERROR} - Logging level (default: WARNING)

[!NOTE] Plain --login still has no visible window in Docker. Add --login-viewer and publish 127.0.0.1:6080:6080 only for the one-shot login command. Docker is already headed by default, so --no-headless changes nothing. The experimental --daemon is ignored in Docker because its owner can outlive the virtual display.

HTTP Mode Example (for web-based MCP clients):

Bash / macOS / Linux:

bash
docker run -it --rm \
  -v ~/.linkedin-mcp:/home/pwuser/.linkedin-mcp \
  -p 127.0.0.1:8080:8080 \
  stickerdaniel/linkedin-mcp-server:latest \
  --transport streamable-http --host 0.0.0.0 --port 8080 --path /mcp

PowerShell (Windows):

powershell
$sessionDir = Join-Path $env:USERPROFILE ".linkedin-mcp"
docker run -it --rm `
  -v "${sessionDir}:/home/pwuser/.linkedin-mcp" `
  -p 127.0.0.1:8080:8080 `
  stickerdaniel/linkedin-mcp-server:latest `
  --transport streamable-http --host 0.0.0.0 --port 8080 --path /mcp

Both halves of that are needed, and they do different jobs. --host 0.0.0.0 makes the server reachable inside the container: a process bound to 127.0.0.1 in there cannot be reached through a published port at all. The 127.0.0.1: in front of -p is what limits it outside, to this machine. Drop that prefix and Docker publishes on every interface, which puts an endpoint with no authentication on your network. The server cannot tell the two apart, so it warns either way.

Loopback publishing limits this to the machine, not to the container. Other containers on the same host can still reach it through host.docker.internal wherever that name resolves, which is the default on Docker Desktop and OrbStack but not on native Linux Docker.

Runtime server logs are emitted by FastMCP/Uvicorn.

The HTTP server answers requests addressed to localhost or to the address it is bound to, and refuses others with 421. That is what stops a website you merely visit from pointing a domain at this server and using your LinkedIn session through your own browser.

Reaching the server by any other name is refused, including a machine name on your network and the public name in front of a reverse proxy. Either have the proxy rewrite the upstream Host to the backend address, or name the host you serve it under:

bash
FASTMCP_HTTP_ALLOWED_HOSTS='["mcp.example"]'

That permits exactly that name and keeps refusing everything else. The endpoint still has no authentication, so anything reachable beyond your own machine belongs behind something that provides it.

Test with mcp inspector:

  1. Install and run mcp inspector bunx @modelcontextprotocol/inspector
  2. Click pre-filled token url to open the inspector in your browser
  3. Select Streamable HTTP as Transport Type
  4. Set URL to http://localhost:8080/mcp
  5. Connect
  6. Test tools
  • Make sure Docker is installed
  • Check if Docker is running: docker ps
  • Permission errors on ~/.linkedin-mcp: an older rootful Docker run may have created the directory as root. Fix it with sudo chown -R "$(id -u):$(id -g)" ~/.linkedin-mcp.
  • Make sure you have only one active LinkedIn session at a time
  • LinkedIn may require a login confirmation in the LinkedIn mobile app for --login
  • LinkedIn may show a captcha challenge during login. Run uvx mcp-server-linkedin@latest --login which opens a browser where you can solve captchas manually. See the uvx setup for prerequisites.
  • If Docker auth becomes stale after you re-login on the host, restart Docker once so it can fresh-bridge from the new source session generation.
  • Page operations failing (elements not found, navigation hangs): increase the browser page-op timeout: --timeout 10000 or TIMEOUT=10000 (milliseconds, default 5000).
  • Entire tool calls timing out (e.g. multi-section profiles, cold-start Chromium, slow containers): increase the per-tool execution timeout: --tool-timeout 300 or TOOL_TIMEOUT=300 (seconds, default 180).
  • First tool call with no session: if a locally logged-in browser has a live LinkedIn session, the server auto-imports it (see AUTO_IMPORT_FROM_BROWSER / --auto-import) instead of forcing a manual login. On macOS the keychain may prompt once for Safe Storage access. If no importable browser session exists, it falls back to opening a login window and waits up to LOGIN_INLINE_WAIT seconds (default 25, max 45; --login-inline-wait) so a quick sign-in resolves in one call. If the wait elapses, the tool returns a pending signal and the model retries in about 30 seconds. Neither the auto-import nor the inline wait applies under Docker or when the server is bound to a non-loopback HTTP host. Create the session on the host with --login, or use the explicit Docker --login --login-viewer command.
  • Users on slow connections may need higher values for either.
  • If tool calls answer "No valid LinkedIn session is available in Docker" on a machine that is not a container, the runtime was misdetected. This happened on Linux hosts running a Docker daemon for unrelated services. Set LINKEDIN_MCP_CONTAINER=false to override the detection; true forces the opposite.
  • If Chrome is installed in a non-standard location, use --chrome-path /path/to/chrome
  • Can also set via environment variable: CHROME_PATH=/path/to/chrome
  • On macOS and Linux the browser must be at least as new as the one that last opened your profile, and the server refuses the launch otherwise. (Not on Windows: a browser there cannot be asked its version without starting one, so the check is off.) An older browser can silently drop stores a newer one wrote, the saved session among them, and the failure then looks exactly like an expired login. The message names both versions. Going back to the bundled Chromium after running a newer Chrome once is the usual way to meet this; either run the newer browser again, whichever one that was, or run --login, which moves the stored session aside and signs in fresh with the browser you have. --logout also clears it but discards the old session instead of keeping it recoverable, and it asks for confirmation on the terminal, so it is not usable from a server an MCP client started.
  • Only Chrome, Chromium and Chrome for Testing are compared this way. Forks number themselves differently (Vivaldi is on 7.x, Edge's build number sits far below Chrome's under the same major), so pointing CHROME_PATH at one turns the check off rather than producing a refusal nothing could satisfy.
  • In the documented Docker setup this check does not apply. The container never opens the profile you created with --login; it derives its own from your cookies, and by default rebuilds that from scratch on every start, so there is nothing for an older image to downgrade. With EXPERIMENTAL_PERSIST_DERIVED_RUNTIME the derived profile is kept, and an image tag that moves backwards then throws it away and re-derives it, again with nothing for you to do. The check matters on the host, where the server opens that profile directly. Not during --login itself, which moves the old profile aside before it starts a browser and so can never trip it.

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LinkedIn scores the address a session signs in from. Your account's usual IP address is the safe one. You should use a proxy in your country when the server cannot use it: a VPS, another country, or a second account that must not share the first one's address.

With a paid provider, use a sticky residential session that holds one address (never per-request rotation). A WireGuard full tunnel or Tailscale exit node on your home network works when the server should use your usual home address.

Setup:

  • Set the proxy up before --login. Moving an existing session to a new address triggers a LinkedIn checkpoint. That includes a session from --import-from-browser, which was created on your real address.
  • --proxy-server scheme://host:port or PROXY_SERVER, with http, https, socks4 or socks5. Only browser traffic is routed, not the MCP transport.
  • Pass credentials through PROXY_USERNAME and PROXY_PASSWORD, or include them in PROXY_SERVER using the combined http://user:pass@host:port form. The combined form is not accepted by the --proxy-server CLI option.
  • PROXY_BYPASS=localhost,127.0.0.1,::1 reaches local targets directly. With a proxy set, Chromium routes localhost through it too.
  • Chromium cannot authenticate to a SOCKS proxy, so credentials require an http(s) endpoint. If your provider only offers authenticated SOCKS5, run a local relay that holds the credentials and point the server at that.
  • A wrong proxy password shows up as a timeout or a failed sign-in, because Chromium retries the authentication challenge until the page times out. If sessions stop working right after you add a proxy, check the proxy credentials first.
  • Auto-import is skipped while a proxy is configured: the imported session would move from your real address to the proxy. Use --login.
  • Inside a container 127.0.0.1 is the container itself, so a relay on the host is host.docker.internal; native Linux Docker also needs --add-host=host.docker.internal:host-gateway.

🐍 Local Setup (Develop & Contribute)

Contributions are welcome! See CONTRIBUTING.md for architecture guidelines and checklists. Packet: search first, then add evidence to an existing issue or prepare a new report. Agents follow the packet skill. Humans use the issue forms.

Prerequisites: Git and uv installed

Installation

bash
# 1. Clone repository
git clone https://github.com/stickerdaniel/linkedin-mcp-server
cd linkedin-mcp-server

# 2. Install UV package manager (if not already installed)
curl -LsSf https://astral.sh/uv/install.sh | sh

# 3. Install dependencies
uv sync
uv sync --group dev

# 4. Install pre-commit hooks
uv run pre-commit install

# 5. Start the server
uv run -m linkedin_mcp_server

Local Setup Help

Session:

  • --login - Open a browser to sign in and save the session
  • --import-from-browser [BROWSER] - Reuse a session from a locally signed-in Chromium browser (chrome, chromium, brave, edge, arc, vivaldi, helium, yandex, whale, auto). Bare flag picks auto, the most recently used browser with a live LinkedIn session.
  • --auto-import / --no-auto-import - Import a session from a signed-in local browser on the first tool call that needs one, before falling back to manual login (default: on). Skipped in Docker, behind a proxy, and on a non-loopback HTTP bind. On macOS the keychain may prompt once.
  • --status - Check whether the stored session is valid, then exit
  • --logout - Clear the stored session
  • --user-data-dir PATH - Browser profile directory (default: ~/.linkedin-mcp/profile). Rotating or clearing a session deletes this directory and its parent, which holds the stored cookies and derived profiles.
  • --claim-profile-root - Take over a profile directory the server will not claim on its own, such as one whose parent already holds other files. Needed once per directory.

Transport:

  • --transport {stdio,streamable-http} - Force the transport mode (default: stdio)
  • --host HOST / --port PORT / --path PATH - HTTP server address (defaults: 127.0.0.1, 8000, /mcp)

Timeouts:

  • --timeout MS - Timeout for a single page operation (default: 5000)
  • --tool-timeout SECONDS - Timeout for a whole tool call (default: 180). Raise it for heavy scrapes, slow networks, or a cold-start browser.
  • --login-timeout SECONDS - How long the login browser waits for you to finish signing in (default: 1800; 0 = no limit). --login-viewer ends the session after 30 minutes either way.
  • --login-inline-wait SECONDS - How long a tool call waits for a login to finish before telling the model to retry (default: 25, max 45; 0 = return at once)

Shared browser:

  • --browser-wait SECONDS - How long to wait for another server process to hand over the shared browser (default: 25, max 45; 0 = report busy at once). Only matters with several MCP clients running at once.
  • --browser-min-hold SECONDS - Shortest time this process keeps the shared browser before handing it over (default: 20). Clamped to 3 seconds below --browser-wait, so raise that one along with it. Higher means fewer browser restarts but longer waits for other clients.
  • --browser-idle-timeout SECONDS - Close an idle browser and release the profile after this long without a tool call (default: 600; 0 = keep it open)

Browser:

  • --no-headless - Show the browser window (useful for debugging)
  • --slow-mo MS - Delay between browser actions (default: 0, useful for debugging)
  • --viewport WxH - Viewport size (default: 1280x720). Applies to windowless mode only; a headed launch uses the real window size.
  • --chrome-path PATH - Path to a Chrome/Chromium executable
  • --installer-temp-dir PATH - Parent directory for temporary files created during browser installation bootstrap (default: system temporary directory). Useful when system %TEMP% ancestry has non-standard ACLs or permissions.
  • --proxy-server URL - Route browser traffic through a proxy, as scheme://host:port. Set it up before --login; see Using a proxy.

Other:

  • --log-level {DEBUG,INFO,WARNING,ERROR} - Logging level (default: WARNING)
  • --help - Show help

Note: Most CLI options have environment variable equivalents. See .env.example for details.

HTTP Mode Example (for web-based MCP clients):

bash
uv run -m linkedin_mcp_server --transport streamable-http --host 127.0.0.1 --port 8000 --path /mcp

Claude Desktop:

json
{
  "mcpServers": {
    "mcp-server-linkedin": {
      "command": "uv",
      "args": ["--directory", "/path/to/linkedin-mcp-server", "run", "-m", "linkedin_mcp_server"]
    }
  }
}

stdio is used by default for this config.

  • Make sure you have only one active LinkedIn session at a time
  • LinkedIn may require a login confirmation in the LinkedIn mobile app for --login
  • LinkedIn may show a captcha challenge during login. The --login command opens a browser where you can solve it manually.
  • Use --no-headless to see browser actions and debug scraping problems
  • Add --log-level DEBUG to see more detailed logging
  • Browser profile is stored at ~/.linkedin-mcp/profile/
  • Managed browser downloads are cached at ~/.linkedin-mcp/patchright-browsers/, shared with the uvx and MCP Bundle installations
  • The browser cache keeps growing: Patchright keeps an old Chromium revision for as long as any installed version still references it, and a uv archive or a second worktree is such a reference. The server logs a warning naming what it holds. To reclaim the space, stop every LinkedIn MCP Server instance, delete ~/.linkedin-mcp/patchright-browsers/, and let the next launch download the current browser.
  • Use --logout to clear the profile and start fresh
  • Check Python version: python --version (should be 3.12.4+)
  • Reinstall Patchright: uv run patchright install chromium
  • Reinstall dependencies: uv sync --reinstall
  • Page operations failing (elements not found, navigation hangs): increase the browser page-op timeout: --timeout 10000 or TIMEOUT=10000 (milliseconds, default 5000).
  • Entire tool calls timing out (e.g. multi-section profiles, cold-start Chromium, slow containers): increase the per-tool execution timeout: --tool-timeout 300 or TOOL_TIMEOUT=300 (seconds, default 180).
  • First tool call with no session: if a locally logged-in browser has a live LinkedIn session, the server auto-imports it (see AUTO_IMPORT_FROM_BROWSER / --auto-import) instead of for

Use LinkedIn MCP MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once LinkedIn MCP is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add LinkedIn MCP as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the LinkedIn MCP MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "linkedin-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "<mcp-server-package>"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the LinkedIn MCP MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the LinkedIn MCP MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use LinkedIn MCP to help me with this task?
LinkedIn MCP
Sure. I read it.
Here is what I found using LinkedIn MCP.

Frequently asked questions

What is the LinkedIn MCP MCP server used for?

LinkedIn MCP is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use LinkedIn MCP MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use LinkedIn MCP with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use LinkedIn MCP MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With LinkedIn MCP connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect LinkedIn MCP MCP to TypingMind?

LinkedIn MCP runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does LinkedIn MCP MCP provide in TypingMind?

LinkedIn MCP exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use LinkedIn MCP MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If LinkedIn MCP requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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